From 4b97060d85c8d31b574e412e26ba36ee94fffe20 Mon Sep 17 00:00:00 2001
From: "nikbel2004@outlook.com" <nikbel2004@outlook.com>
Date: Mon, 10 Feb 2025 01:15:06 +0400
Subject: [PATCH] laboratory_7

---
 laboratory_7/lab7.ipynb       | 4130 +++++++++++++++++++++++++++++++++
 laboratory_7/requirements.txt |   40 +
 2 files changed, 4170 insertions(+)
 create mode 100644 laboratory_7/lab7.ipynb
 create mode 100644 laboratory_7/requirements.txt

diff --git a/laboratory_7/lab7.ipynb b/laboratory_7/lab7.ipynb
new file mode 100644
index 0000000..61fd7a4
--- /dev/null
+++ b/laboratory_7/lab7.ipynb
@@ -0,0 +1,4130 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Приступаем к работе..."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Index(['id', 'date', 'price', 'bedrooms', 'bathrooms', 'sqft_living',\n",
+       "       'sqft_lot', 'floors', 'waterfront', 'view', 'condition', 'grade',\n",
+       "       'sqft_above', 'sqft_basement', 'yr_built', 'yr_renovated', 'zipcode',\n",
+       "       'lat', 'long', 'sqft_living15', 'sqft_lot15'],\n",
+       "      dtype='object')"
+      ]
+     },
+     "execution_count": 69,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "import skfuzzy as fuzz\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "\n",
+    "df_house = pd.read_csv(\".//static//csv//kc_house_data.csv\")\n",
+    "df_house.columns\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 70,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>date</th>\n",
+       "      <th>price</th>\n",
+       "      <th>bedrooms</th>\n",
+       "      <th>bathrooms</th>\n",
+       "      <th>sqft_living</th>\n",
+       "      <th>sqft_lot</th>\n",
+       "      <th>floors</th>\n",
+       "      <th>waterfront</th>\n",
+       "      <th>view</th>\n",
+       "      <th>...</th>\n",
+       "      <th>grade</th>\n",
+       "      <th>sqft_above</th>\n",
+       "      <th>sqft_basement</th>\n",
+       "      <th>yr_built</th>\n",
+       "      <th>yr_renovated</th>\n",
+       "      <th>zipcode</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>long</th>\n",
+       "      <th>sqft_living15</th>\n",
+       "      <th>sqft_lot15</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>7129300520</td>\n",
+       "      <td>20141013T000000</td>\n",
+       "      <td>221900.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>1180</td>\n",
+       "      <td>5650</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1180</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1955</td>\n",
+       "      <td>0</td>\n",
+       "      <td>98178</td>\n",
+       "      <td>47.5112</td>\n",
+       "      <td>-122.257</td>\n",
+       "      <td>1340</td>\n",
+       "      <td>5650</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>6414100192</td>\n",
+       "      <td>20141209T000000</td>\n",
+       "      <td>538000.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2.25</td>\n",
+       "      <td>2570</td>\n",
+       "      <td>7242</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7</td>\n",
+       "      <td>2170</td>\n",
+       "      <td>400</td>\n",
+       "      <td>1951</td>\n",
+       "      <td>1991</td>\n",
+       "      <td>98125</td>\n",
+       "      <td>47.7210</td>\n",
+       "      <td>-122.319</td>\n",
+       "      <td>1690</td>\n",
+       "      <td>7639</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>5631500400</td>\n",
+       "      <td>20150225T000000</td>\n",
+       "      <td>180000.0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1.00</td>\n",
+       "      <td>770</td>\n",
+       "      <td>10000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>6</td>\n",
+       "      <td>770</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1933</td>\n",
+       "      <td>0</td>\n",
+       "      <td>98028</td>\n",
+       "      <td>47.7379</td>\n",
+       "      <td>-122.233</td>\n",
+       "      <td>2720</td>\n",
+       "      <td>8062</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2487200875</td>\n",
+       "      <td>20141209T000000</td>\n",
+       "      <td>604000.0</td>\n",
+       "      <td>4</td>\n",
+       "      <td>3.00</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>5000</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7</td>\n",
+       "      <td>1050</td>\n",
+       "      <td>910</td>\n",
+       "      <td>1965</td>\n",
+       "      <td>0</td>\n",
+       "      <td>98136</td>\n",
+       "      <td>47.5208</td>\n",
+       "      <td>-122.393</td>\n",
+       "      <td>1360</td>\n",
+       "      <td>5000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1954400510</td>\n",
+       "      <td>20150218T000000</td>\n",
+       "      <td>510000.0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>8080</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>8</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1987</td>\n",
+       "      <td>0</td>\n",
+       "      <td>98074</td>\n",
+       "      <td>47.6168</td>\n",
+       "      <td>-122.045</td>\n",
+       "      <td>1800</td>\n",
+       "      <td>7503</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           id             date     price  bedrooms  bathrooms  sqft_living  \\\n",
+       "0  7129300520  20141013T000000  221900.0         3       1.00         1180   \n",
+       "1  6414100192  20141209T000000  538000.0         3       2.25         2570   \n",
+       "2  5631500400  20150225T000000  180000.0         2       1.00          770   \n",
+       "3  2487200875  20141209T000000  604000.0         4       3.00         1960   \n",
+       "4  1954400510  20150218T000000  510000.0         3       2.00         1680   \n",
+       "\n",
+       "   sqft_lot  floors  waterfront  view  ...  grade  sqft_above  sqft_basement  \\\n",
+       "0      5650     1.0           0     0  ...      7        1180              0   \n",
+       "1      7242     2.0           0     0  ...      7        2170            400   \n",
+       "2     10000     1.0           0     0  ...      6         770              0   \n",
+       "3      5000     1.0           0     0  ...      7        1050            910   \n",
+       "4      8080     1.0           0     0  ...      8        1680              0   \n",
+       "\n",
+       "   yr_built  yr_renovated  zipcode      lat     long  sqft_living15  \\\n",
+       "0      1955             0    98178  47.5112 -122.257           1340   \n",
+       "1      1951          1991    98125  47.7210 -122.319           1690   \n",
+       "2      1933             0    98028  47.7379 -122.233           2720   \n",
+       "3      1965             0    98136  47.5208 -122.393           1360   \n",
+       "4      1987             0    98074  47.6168 -122.045           1800   \n",
+       "\n",
+       "   sqft_lot15  \n",
+       "0        5650  \n",
+       "1        7639  \n",
+       "2        8062  \n",
+       "3        5000  \n",
+       "4        7503  \n",
+       "\n",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 70,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_house.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 71,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>id</th>\n",
+       "      <th>price</th>\n",
+       "      <th>bedrooms</th>\n",
+       "      <th>bathrooms</th>\n",
+       "      <th>sqft_living</th>\n",
+       "      <th>sqft_lot</th>\n",
+       "      <th>floors</th>\n",
+       "      <th>waterfront</th>\n",
+       "      <th>view</th>\n",
+       "      <th>condition</th>\n",
+       "      <th>grade</th>\n",
+       "      <th>sqft_above</th>\n",
+       "      <th>sqft_basement</th>\n",
+       "      <th>yr_built</th>\n",
+       "      <th>yr_renovated</th>\n",
+       "      <th>zipcode</th>\n",
+       "      <th>lat</th>\n",
+       "      <th>long</th>\n",
+       "      <th>sqft_living15</th>\n",
+       "      <th>sqft_lot15</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>2.161300e+04</td>\n",
+       "      <td>2.161300e+04</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>2.161300e+04</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "      <td>21613.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>4.580302e+09</td>\n",
+       "      <td>5.400881e+05</td>\n",
+       "      <td>3.370842</td>\n",
+       "      <td>2.114757</td>\n",
+       "      <td>2079.899736</td>\n",
+       "      <td>1.510697e+04</td>\n",
+       "      <td>1.494309</td>\n",
+       "      <td>0.007542</td>\n",
+       "      <td>0.234303</td>\n",
+       "      <td>3.409430</td>\n",
+       "      <td>7.656873</td>\n",
+       "      <td>1788.390691</td>\n",
+       "      <td>291.509045</td>\n",
+       "      <td>1971.005136</td>\n",
+       "      <td>84.402258</td>\n",
+       "      <td>98077.939805</td>\n",
+       "      <td>47.560053</td>\n",
+       "      <td>-122.213896</td>\n",
+       "      <td>1986.552492</td>\n",
+       "      <td>12768.455652</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>2.876566e+09</td>\n",
+       "      <td>3.671272e+05</td>\n",
+       "      <td>0.930062</td>\n",
+       "      <td>0.770163</td>\n",
+       "      <td>918.440897</td>\n",
+       "      <td>4.142051e+04</td>\n",
+       "      <td>0.539989</td>\n",
+       "      <td>0.086517</td>\n",
+       "      <td>0.766318</td>\n",
+       "      <td>0.650743</td>\n",
+       "      <td>1.175459</td>\n",
+       "      <td>828.090978</td>\n",
+       "      <td>442.575043</td>\n",
+       "      <td>29.373411</td>\n",
+       "      <td>401.679240</td>\n",
+       "      <td>53.505026</td>\n",
+       "      <td>0.138564</td>\n",
+       "      <td>0.140828</td>\n",
+       "      <td>685.391304</td>\n",
+       "      <td>27304.179631</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>1.000102e+06</td>\n",
+       "      <td>7.500000e+04</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>290.000000</td>\n",
+       "      <td>5.200000e+02</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>290.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1900.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>98001.000000</td>\n",
+       "      <td>47.155900</td>\n",
+       "      <td>-122.519000</td>\n",
+       "      <td>399.000000</td>\n",
+       "      <td>651.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>2.123049e+09</td>\n",
+       "      <td>3.219500e+05</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>1.750000</td>\n",
+       "      <td>1427.000000</td>\n",
+       "      <td>5.040000e+03</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>1190.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1951.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>98033.000000</td>\n",
+       "      <td>47.471000</td>\n",
+       "      <td>-122.328000</td>\n",
+       "      <td>1490.000000</td>\n",
+       "      <td>5100.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>3.904930e+09</td>\n",
+       "      <td>4.500000e+05</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>2.250000</td>\n",
+       "      <td>1910.000000</td>\n",
+       "      <td>7.618000e+03</td>\n",
+       "      <td>1.500000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>3.000000</td>\n",
+       "      <td>7.000000</td>\n",
+       "      <td>1560.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>1975.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>98065.000000</td>\n",
+       "      <td>47.571800</td>\n",
+       "      <td>-122.230000</td>\n",
+       "      <td>1840.000000</td>\n",
+       "      <td>7620.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>7.308900e+09</td>\n",
+       "      <td>6.450000e+05</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>2.500000</td>\n",
+       "      <td>2550.000000</td>\n",
+       "      <td>1.068800e+04</td>\n",
+       "      <td>2.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>2210.000000</td>\n",
+       "      <td>560.000000</td>\n",
+       "      <td>1997.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>98118.000000</td>\n",
+       "      <td>47.678000</td>\n",
+       "      <td>-122.125000</td>\n",
+       "      <td>2360.000000</td>\n",
+       "      <td>10083.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>9.900000e+09</td>\n",
+       "      <td>7.700000e+06</td>\n",
+       "      <td>33.000000</td>\n",
+       "      <td>8.000000</td>\n",
+       "      <td>13540.000000</td>\n",
+       "      <td>1.651359e+06</td>\n",
+       "      <td>3.500000</td>\n",
+       "      <td>1.000000</td>\n",
+       "      <td>4.000000</td>\n",
+       "      <td>5.000000</td>\n",
+       "      <td>13.000000</td>\n",
+       "      <td>9410.000000</td>\n",
+       "      <td>4820.000000</td>\n",
+       "      <td>2015.000000</td>\n",
+       "      <td>2015.000000</td>\n",
+       "      <td>98199.000000</td>\n",
+       "      <td>47.777600</td>\n",
+       "      <td>-121.315000</td>\n",
+       "      <td>6210.000000</td>\n",
+       "      <td>871200.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                 id         price      bedrooms     bathrooms   sqft_living  \\\n",
+       "count  2.161300e+04  2.161300e+04  21613.000000  21613.000000  21613.000000   \n",
+       "mean   4.580302e+09  5.400881e+05      3.370842      2.114757   2079.899736   \n",
+       "std    2.876566e+09  3.671272e+05      0.930062      0.770163    918.440897   \n",
+       "min    1.000102e+06  7.500000e+04      0.000000      0.000000    290.000000   \n",
+       "25%    2.123049e+09  3.219500e+05      3.000000      1.750000   1427.000000   \n",
+       "50%    3.904930e+09  4.500000e+05      3.000000      2.250000   1910.000000   \n",
+       "75%    7.308900e+09  6.450000e+05      4.000000      2.500000   2550.000000   \n",
+       "max    9.900000e+09  7.700000e+06     33.000000      8.000000  13540.000000   \n",
+       "\n",
+       "           sqft_lot        floors    waterfront          view     condition  \\\n",
+       "count  2.161300e+04  21613.000000  21613.000000  21613.000000  21613.000000   \n",
+       "mean   1.510697e+04      1.494309      0.007542      0.234303      3.409430   \n",
+       "std    4.142051e+04      0.539989      0.086517      0.766318      0.650743   \n",
+       "min    5.200000e+02      1.000000      0.000000      0.000000      1.000000   \n",
+       "25%    5.040000e+03      1.000000      0.000000      0.000000      3.000000   \n",
+       "50%    7.618000e+03      1.500000      0.000000      0.000000      3.000000   \n",
+       "75%    1.068800e+04      2.000000      0.000000      0.000000      4.000000   \n",
+       "max    1.651359e+06      3.500000      1.000000      4.000000      5.000000   \n",
+       "\n",
+       "              grade    sqft_above  sqft_basement      yr_built  yr_renovated  \\\n",
+       "count  21613.000000  21613.000000   21613.000000  21613.000000  21613.000000   \n",
+       "mean       7.656873   1788.390691     291.509045   1971.005136     84.402258   \n",
+       "std        1.175459    828.090978     442.575043     29.373411    401.679240   \n",
+       "min        1.000000    290.000000       0.000000   1900.000000      0.000000   \n",
+       "25%        7.000000   1190.000000       0.000000   1951.000000      0.000000   \n",
+       "50%        7.000000   1560.000000       0.000000   1975.000000      0.000000   \n",
+       "75%        8.000000   2210.000000     560.000000   1997.000000      0.000000   \n",
+       "max       13.000000   9410.000000    4820.000000   2015.000000   2015.000000   \n",
+       "\n",
+       "            zipcode           lat          long  sqft_living15     sqft_lot15  \n",
+       "count  21613.000000  21613.000000  21613.000000   21613.000000   21613.000000  \n",
+       "mean   98077.939805     47.560053   -122.213896    1986.552492   12768.455652  \n",
+       "std       53.505026      0.138564      0.140828     685.391304   27304.179631  \n",
+       "min    98001.000000     47.155900   -122.519000     399.000000     651.000000  \n",
+       "25%    98033.000000     47.471000   -122.328000    1490.000000    5100.000000  \n",
+       "50%    98065.000000     47.571800   -122.230000    1840.000000    7620.000000  \n",
+       "75%    98118.000000     47.678000   -122.125000    2360.000000   10083.000000  \n",
+       "max    98199.000000     47.777600   -121.315000    6210.000000  871200.000000  "
+      ]
+     },
+     "execution_count": 71,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_house.describe()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 72,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "id               0\n",
+      "date             0\n",
+      "price            0\n",
+      "bedrooms         0\n",
+      "bathrooms        0\n",
+      "sqft_living      0\n",
+      "sqft_lot         0\n",
+      "floors           0\n",
+      "waterfront       0\n",
+      "view             0\n",
+      "condition        0\n",
+      "grade            0\n",
+      "sqft_above       0\n",
+      "sqft_basement    0\n",
+      "yr_built         0\n",
+      "yr_renovated     0\n",
+      "zipcode          0\n",
+      "lat              0\n",
+      "long             0\n",
+      "sqft_living15    0\n",
+      "sqft_lot15       0\n",
+      "dtype: int64\n",
+      "id               False\n",
+      "date             False\n",
+      "price            False\n",
+      "bedrooms         False\n",
+      "bathrooms        False\n",
+      "sqft_living      False\n",
+      "sqft_lot         False\n",
+      "floors           False\n",
+      "waterfront       False\n",
+      "view             False\n",
+      "condition        False\n",
+      "grade            False\n",
+      "sqft_above       False\n",
+      "sqft_basement    False\n",
+      "yr_built         False\n",
+      "yr_renovated     False\n",
+      "zipcode          False\n",
+      "lat              False\n",
+      "long             False\n",
+      "sqft_living15    False\n",
+      "sqft_lot15       False\n",
+      "dtype: bool\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Процент пропущенных значений признаков\n",
+    "for i in df_house.columns:\n",
+    "    null_rate = df_house[i].isnull().sum() / len(df_house) * 100\n",
+    "    if null_rate > 0:\n",
+    "        print(f'{i} Процент пустых значений: %{null_rate:.2f}')\n",
+    "\n",
+    "print(df_house.isnull().sum())\n",
+    "\n",
+    "print(df_house.isnull().any())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 73,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "id                 int64\n",
+       "date              object\n",
+       "price            float64\n",
+       "bedrooms           int64\n",
+       "bathrooms        float64\n",
+       "sqft_living        int64\n",
+       "sqft_lot           int64\n",
+       "floors           float64\n",
+       "waterfront         int64\n",
+       "view               int64\n",
+       "condition          int64\n",
+       "grade              int64\n",
+       "sqft_above         int64\n",
+       "sqft_basement      int64\n",
+       "yr_built           int64\n",
+       "yr_renovated       int64\n",
+       "zipcode            int64\n",
+       "lat              float64\n",
+       "long             float64\n",
+       "sqft_living15      int64\n",
+       "sqft_lot15         int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 73,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Проверка типов столбцов\n",
+    "df_house.dtypes"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Определим входные и выходные переменные (данные)  \n",
+    "\n",
+    "Перед построением нечёткой системы, нужно определить, какие переменные будут входными, а какие - выходными.\n",
+    "\n",
+    "**Входные переменные (fuzzy inputs)**  \n",
+    "Входные X: bathrooms - ванные, sqft_living - площадь  \n",
+    "\n",
+    "**Выходные переменные (fuzzy output)**  \n",
+    "Выходные Y: price - цены.  \n",
+    "\n",
+    "## Настройка лингвистических переменных  \n",
+    "Заключается в определении термов, которые будут соответствовать переменным, ну и их тип. (Какие-то будут функциями принадлежности, другие треугольными).\n",
+    "\n",
+    "Всем параметрам присваиваются значения low, medium, high\n",
+    "\n",
+    "**Создадим лингвистические переменные**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 74,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from skfuzzy import control as ctrl\n",
+    "\n",
+    "# Определим входные и выходные переменные\n",
+    "sqft_living = ctrl.Antecedent(df_house['sqft_living'].sort_values(), \"sqft_living\")\n",
+    "bathrooms = ctrl.Antecedent(df_house['bathrooms'].sort_values(), \"bathrooms\")\n",
+    "price = ctrl.Consequent(df_house['price'].sort_values(), \"price\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Формирование нечётких переменных для лингвистических переменных  \n",
+    "Определение функций принадлежности"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "e:\\MII\\laboratory\\mai\\Lib\\site-packages\\skfuzzy\\control\\fuzzyvariable.py:125: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
+      "  fig.show()\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sqft_living['low'] = fuzz.zmf(sqft_living.universe, 0, 6000)\n",
+    "sqft_living['medium'] = fuzz.trapmf(sqft_living.universe, [3400, 5700, 7800, 9900])\n",
+    "sqft_living['high'] = fuzz.trimf(sqft_living.universe, [8000, 11580, 14860])\n",
+    "sqft_living.view()\n",
+    "\n",
+    "bathrooms['low'] = fuzz.zmf(bathrooms.universe, 0, 3)\n",
+    "bathrooms['medium'] = fuzz.trapmf(bathrooms.universe, [1, 3, 4, 7])\n",
+    "bathrooms['high'] = fuzz.trimf(bathrooms.universe, [5, 9, 12])\n",
+    "bathrooms.view()\n",
+    "\n",
+    "price['low'] = fuzz.zmf(price.universe, 0, 2500000)\n",
+    "price['medium'] = fuzz.trapmf(price.universe, [1500000, 3000000, 5000000, 6000000])\n",
+    "price['high'] = fuzz.trimf(price.universe, [4000000, 9000000, 11000000])\n",
+    "#price.automf(5, variable_type=\"quant\") Для подробного анализа\n",
+    "price.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Формирование и визуализация базы нечётких правил  \n",
+    "Определение правил: установим логические зависимости между входными и выходными переменными.  \n",
+    "\n",
+    "**Правила:**  \n",
+    "&nbsp;&nbsp; 1. Если количество ванн маленькое и площадь маленькая, то цена дешёвая  \n",
+    "&nbsp;&nbsp; 2. Если количество ванн маленькое и площадь средняя, то цена средняя  \n",
+    "&nbsp;&nbsp; 3. Если количество ванн маленькое и площадь большая, то цена высокая  \n",
+    "&nbsp;&nbsp; 4. Если количество ванн среднее и площадь маленькая, то цена средняя  \n",
+    "&nbsp;&nbsp; 5. Если количество ванн среднее и площадь средняя, то цена средняя  \n",
+    "&nbsp;&nbsp; 6. Если количество ванн среднее и площадь большая, то цена высокая  \n",
+    "&nbsp;&nbsp; 7. Если количество ванн большое и площадь маленькая, то цена дешёвая  \n",
+    "&nbsp;&nbsp; 8. Если количество ванн большое и площадь средняя, то цена средняя  \n",
+    "&nbsp;&nbsp; 9. Если количество ванн большое и площадь большая, то цена высокая  \n",
+    "\n",
+    "В случае ошибки необходимо в файле  \n",
+    "\n",
+    ".venv/lib/python3.13/site-packages/skfuzzy/control/visualization.py  \n",
+    "удалить лишний отступ на 182 строке, должно быть:  \n",
+    "\n",
+    "if not matplotlib_present:  \n",
+    "&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;    raise ImportError(\"`ControlSystemVisualizer` can only be used \"  \n",
+    "&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;  \"with `matplotlib` present in the system.\")  \n",
+    "\n",
+    "self.ctrl = control_system  \n",
+    "\n",
+    "self.fig, self.ax = plt.subplots()  \n",
+    "\n",
+    "После этого обязательно перезапустить ядро!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 76,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<Figure size 640x480 with 1 Axes>, <Axes: >)"
+      ]
+     },
+     "execution_count": 76,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Для сформированных нечётких переменных поработаем с нечёткими правилами (bathrooms, sqft_living, price)\n",
+    "rule1 = ctrl.Rule(bathrooms['low'] & sqft_living['low'], price['low'])\n",
+    "rule2 = ctrl.Rule(bathrooms['low'] & sqft_living['medium'], price['medium'])\n",
+    "rule3 = ctrl.Rule(bathrooms['low'] & sqft_living['high'], price['medium'])\n",
+    "rule4 = ctrl.Rule(bathrooms['medium'] & sqft_living['low'], price['medium'])\n",
+    "rule5 = ctrl.Rule(bathrooms['medium'] & sqft_living['medium'], price['medium'])\n",
+    "rule6 = ctrl.Rule(bathrooms['medium'] & sqft_living['high'], price['high'])\n",
+    "rule7 = ctrl.Rule(bathrooms['high'] & sqft_living['low'], price['low'])\n",
+    "rule8 = ctrl.Rule(bathrooms['high'] & sqft_living['medium'], price['medium'])\n",
+    "rule9 = ctrl.Rule(bathrooms['high'] & sqft_living['high'], price['high'])\n",
+    "\n",
+    "\n",
+    "rule1.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "##### Создание нечёткой системы и добавление нечётких правил в базу знаний нечёткой системы"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 77,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "e:\\MII\\laboratory\\mai\\Lib\\site-packages\\skfuzzy\\control\\controlsystem.py:135: UserWarning: FigureCanvasAgg is non-interactive, and thus cannot be shown\n",
+      "  fig.show()\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "price_ctrl = ctrl.ControlSystem(\n",
+    "    [\n",
+    "        rule1,\n",
+    "        rule2,\n",
+    "        rule3,\n",
+    "        rule4,\n",
+    "        rule5,\n",
+    "        rule6,\n",
+    "        rule7,\n",
+    "        rule8,\n",
+    "        rule9,\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "prices = ctrl.ControlSystemSimulation(price_ctrl)\n",
+    "price_ctrl.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Пример расчёта выходной переменной price на основе входных переменных"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 78,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 1\n",
+      "  - low                             : 0.7777777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 3420\n",
+      "  - low                             : 0.36979999999999996\n",
+      "  - medium                          : 0.008695652173913044\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[low]                                       : 0.36979999999999996\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.36979999999999996\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.36979999999999996\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[medium]                                    : 0.008695652173913044\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.008695652173913044\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.008695652173913044\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[low]                                       : 0.36979999999999996\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.008695652173913044\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.36979999999999996\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.008695652173913044\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 1161947.628726741\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.36979999999999996\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.008695652173913044\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "1161947.628726741\n"
+     ]
+    }
+   ],
+   "source": [
+    "prices.input['bathrooms'] = 1\n",
+    "prices.input['sqft_living'] = 3420\n",
+    "\n",
+    "prices.compute()\n",
+    "prices.print_state()\n",
+    "print(prices.output['price'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Визуализация функции принадлежности для выходной переменной price  \n",
+    "\n",
+    "Функция получена в процессе аккумуляции и используется для дефаззификации значения выходной переменной price"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 79,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "price.view(sim=prices)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Тестирование нечёткой системы"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>bathrooms</th>\n",
+       "      <th>sqft_living</th>\n",
+       "      <th>price</th>\n",
+       "      <th>Pred</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.00</td>\n",
+       "      <td>1180</td>\n",
+       "      <td>221900.0</td>\n",
+       "      <td>8.151029e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2.25</td>\n",
+       "      <td>2570</td>\n",
+       "      <td>538000.0</td>\n",
+       "      <td>3.776812e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.00</td>\n",
+       "      <td>770</td>\n",
+       "      <td>180000.0</td>\n",
+       "      <td>8.151029e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3.00</td>\n",
+       "      <td>1960</td>\n",
+       "      <td>604000.0</td>\n",
+       "      <td>3.987988e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2.00</td>\n",
+       "      <td>1680</td>\n",
+       "      <td>510000.0</td>\n",
+       "      <td>3.573309e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>4.50</td>\n",
+       "      <td>5420</td>\n",
+       "      <td>1225000.0</td>\n",
+       "      <td>3.986649e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>2.25</td>\n",
+       "      <td>1715</td>\n",
+       "      <td>257500.0</td>\n",
+       "      <td>3.776812e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>1.50</td>\n",
+       "      <td>1060</td>\n",
+       "      <td>291850.0</td>\n",
+       "      <td>2.858144e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>1.00</td>\n",
+       "      <td>1780</td>\n",
+       "      <td>229500.0</td>\n",
+       "      <td>8.151029e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>2.50</td>\n",
+       "      <td>1890</td>\n",
+       "      <td>323000.0</td>\n",
+       "      <td>3.901451e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>2.50</td>\n",
+       "      <td>3560</td>\n",
+       "      <td>662500.0</td>\n",
+       "      <td>3.905889e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>1.00</td>\n",
+       "      <td>1160</td>\n",
+       "      <td>468000.0</td>\n",
+       "      <td>8.151029e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>1.00</td>\n",
+       "      <td>1430</td>\n",
+       "      <td>310000.0</td>\n",
+       "      <td>8.151029e+05</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1.75</td>\n",
+       "      <td>1370</td>\n",
+       "      <td>400000.0</td>\n",
+       "      <td>3.287220e+06</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>2.00</td>\n",
+       "      <td>1810</td>\n",
+       "      <td>530000.0</td>\n",
+       "      <td>3.573309e+06</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    bathrooms  sqft_living      price          Pred\n",
+       "0        1.00         1180   221900.0  8.151029e+05\n",
+       "1        2.25         2570   538000.0  3.776812e+06\n",
+       "2        1.00          770   180000.0  8.151029e+05\n",
+       "3        3.00         1960   604000.0  3.987988e+06\n",
+       "4        2.00         1680   510000.0  3.573309e+06\n",
+       "5        4.50         5420  1225000.0  3.986649e+06\n",
+       "6        2.25         1715   257500.0  3.776812e+06\n",
+       "7        1.50         1060   291850.0  2.858144e+06\n",
+       "8        1.00         1780   229500.0  8.151029e+05\n",
+       "9        2.50         1890   323000.0  3.901451e+06\n",
+       "10       2.50         3560   662500.0  3.905889e+06\n",
+       "11       1.00         1160   468000.0  8.151029e+05\n",
+       "12       1.00         1430   310000.0  8.151029e+05\n",
+       "13       1.75         1370   400000.0  3.287220e+06\n",
+       "14       2.00         1810   530000.0  3.573309e+06"
+      ]
+     },
+     "execution_count": 80,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Функция для автоматизации вычисления целевой переменной Y на основе вектора признаков X\n",
+    "def fuzzy_pred(row):\n",
+    "    prices.input['bathrooms'] = row['bathrooms']\n",
+    "    prices.input['sqft_living'] = row['sqft_living']\n",
+    "    prices.compute()\n",
+    "    return prices.output['price']\n",
+    "\n",
+    "res = df_house[['bathrooms', 'sqft_living', 'price']].head(100)\n",
+    "\n",
+    "res['Pred'] = res.apply(fuzzy_pred, axis=1)\n",
+    "\n",
+    "res.head(15)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Успешно выполнилось заполнение данными и предсказание"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Оценка результатов на основе метрик для задачи регрессии"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 81,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'RMSE': 2746099.8246131847,\n",
+       " 'RMAE': 1580.7294758581245,\n",
+       " 'R2': -81.15197820517758}"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import math\n",
+    "from sklearn import metrics\n",
+    "\n",
+    "rmetrics = {}\n",
+    "rmetrics[\"RMSE\"] = math.sqrt(metrics.mean_squared_error(res['price'], res['Pred']))\n",
+    "rmetrics[\"RMAE\"] = math.sqrt(metrics.mean_absolute_error(res['price'], res['Pred']))\n",
+    "rmetrics[\"R2\"] = metrics.r2_score(res['price'], res['Pred'])\n",
+    "\n",
+    "rmetrics"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Визуализация оценки качества нечёткой системы и проверка системы  \n",
+    "\n",
+    "Тестирование работы модели, провеу также, подав тестовые данные, а система определит цену."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 86,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.25\n",
+      "  - low                             : 0.125\n",
+      "  - medium                          : 0.625\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 2070\n",
+      "  - low                             : 0.76195\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[low]                                       : 0.76195\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.125\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.125\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[low]                                       : 0.76195\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.625\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.625\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.76195\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3776812.006111908\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.125\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.625\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 3.0\n",
+      "  - low                             : 0.0\n",
+      "  - medium                          : 1.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 2900\n",
+      "  - low                             : 0.5327777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[low]                                       : 0.5327777777777778\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[low]                                       : 0.5327777777777778\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.5327777777777778\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.5327777777777778\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.5327777777777778\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 4012045.778770892\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.5327777777777778\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.5\n",
+      "  - low                             : 0.05555555555555555\n",
+      "  - medium                          : 0.75\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 3770\n",
+      "  - low                             : 0.2762722222222222\n",
+      "  - medium                          : 0.1608695652173913\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[low]                                       : 0.2762722222222222\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.05555555555555555\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.05555555555555555\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[medium]                                    : 0.1608695652173913\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.05555555555555555\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.05555555555555555\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[low]                                       : 0.2762722222222222\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.2762722222222222\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.2762722222222222\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[medium]                                    : 0.1608695652173913\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.1608695652173913\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.1608695652173913\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.2762722222222222\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.1608695652173913\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3898017.7899890468\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.05555555555555555\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.2762722222222222\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 3.5\n",
+      "  - low                             : 0.0\n",
+      "  - medium                          : 1.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 4560\n",
+      "  - low                             : 0.1152\n",
+      "  - medium                          : 0.5043478260869565\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[low]                                       : 0.1152\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.5043478260869565\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[low]                                       : 0.1152\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.1152\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.1152\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[medium]                                    : 0.5043478260869565\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.5043478260869565\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.5043478260869565\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.1152\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.5043478260869565\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 4017676.5216640085\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.5043478260869565\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.5\n",
+      "  - low                             : 0.05555555555555555\n",
+      "  - medium                          : 0.75\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 2550\n",
+      "  - low                             : 0.63875\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[low]                                       : 0.63875\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.05555555555555555\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.05555555555555555\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[low]                                       : 0.63875\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.63875\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.63875\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.63875\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3898895.2060847664\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.05555555555555555\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.63875\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.0\n",
+      "  - low                             : 0.2222222222222222\n",
+      "  - medium                          : 0.5\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1710\n",
+      "  - low                             : 0.83755\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.2222222222222222\n",
+      "  - sqft_living[low]                                       : 0.83755\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.2222222222222222\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.2222222222222222\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.2222222222222222\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.2222222222222222\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.5\n",
+      "  - sqft_living[low]                                       : 0.83755\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.5\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.5\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.5\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.5\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.83755\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3573309.2257454526\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.2222222222222222\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.5\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.5\n",
+      "  - low                             : 0.05555555555555555\n",
+      "  - medium                          : 0.75\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 2690\n",
+      "  - low                             : 0.5979944444444445\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[low]                                       : 0.5979944444444445\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.05555555555555555\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.05555555555555555\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[low]                                       : 0.5979944444444445\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.5979944444444445\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.5979944444444445\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.5979944444444445\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3898623.9274494657\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.05555555555555555\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.5979944444444445\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.5\n",
+      "  - low                             : 0.05555555555555555\n",
+      "  - medium                          : 0.75\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1800\n",
+      "  - low                             : 0.8200000000000001\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[low]                                       : 0.8200000000000001\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.05555555555555555\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.05555555555555555\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[low]                                       : 0.8200000000000001\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.75\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.75\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.8200000000000001\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3901450.9388564667\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.05555555555555555\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.75\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.5\n",
+      "  - low                             : 0.05555555555555555\n",
+      "  - medium                          : 0.75\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1600\n",
+      "  - low                             : 0.8577777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[low]                                       : 0.8577777777777778\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.05555555555555555\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.05555555555555555\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.05555555555555555\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[low]                                       : 0.8577777777777778\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.75\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.75\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.75\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.8577777777777778\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3901450.9388564667\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.05555555555555555\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.75\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 1.0\n",
+      "  - low                             : 0.7777777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 910\n",
+      "  - low                             : 0.9539944444444445\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[low]                                       : 0.9539944444444445\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.7777777777777778\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.7777777777777778\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[low]                                       : 0.9539944444444445\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.9539944444444445\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 815102.9227350706\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.7777777777777778\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 1.0\n",
+      "  - low                             : 0.7777777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1830\n",
+      "  - low                             : 0.81395\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[low]                                       : 0.81395\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.7777777777777778\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.7777777777777778\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[low]                                       : 0.81395\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.81395\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 815102.9227350706\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.7777777777777778\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 1.75\n",
+      "  - low                             : 0.34722222222222227\n",
+      "  - medium                          : 0.375\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1930\n",
+      "  - low                             : 0.7930611111111111\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.34722222222222227\n",
+      "  - sqft_living[low]                                       : 0.7930611111111111\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.34722222222222227\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.34722222222222227\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.34722222222222227\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.34722222222222227\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.375\n",
+      "  - sqft_living[low]                                       : 0.7930611111111111\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.375\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.375\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.375\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.375\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.7930611111111111\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3287219.8856393476\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.34722222222222227\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.375\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 1.0\n",
+      "  - low                             : 0.7777777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1410\n",
+      "  - low                             : 0.8895500000000001\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[low]                                       : 0.8895500000000001\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.7777777777777778\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.7777777777777778\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[low]                                       : 0.8895500000000001\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.8895500000000001\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 815102.9227350706\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.7777777777777778\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.25\n",
+      "  - low                             : 0.125\n",
+      "  - medium                          : 0.625\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1960\n",
+      "  - low                             : 0.7865777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[low]                                       : 0.7865777777777778\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.125\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.125\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[low]                                       : 0.7865777777777778\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.625\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.625\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.7865777777777778\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3776812.006111908\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.125\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.625\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 1.0\n",
+      "  - low                             : 0.7777777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1140\n",
+      "  - low                             : 0.9278\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[low]                                       : 0.9278\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.7777777777777778\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.7777777777777778\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[low]                                       : 0.9278\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.9278\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 815102.9227350706\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.7777777777777778\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 3.75\n",
+      "  - low                             : 0.0\n",
+      "  - medium                          : 1.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 4130\n",
+      "  - low                             : 0.1942722222222222\n",
+      "  - medium                          : 0.3173913043478261\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[low]                                       : 0.1942722222222222\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.3173913043478261\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[low]                                       : 0.1942722222222222\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.1942722222222222\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.1942722222222222\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[medium]                                    : 0.3173913043478261\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.3173913043478261\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.3173913043478261\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.1942722222222222\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.3173913043478261\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 4075259.915075312\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.3173913043478261\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 1.0\n",
+      "  - low                             : 0.7777777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1430\n",
+      "  - low                             : 0.8863944444444445\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[low]                                       : 0.8863944444444445\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.7777777777777778\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.7777777777777778\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[low]                                       : 0.8863944444444445\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.8863944444444445\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 815102.9227350706\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.7777777777777778\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 3.25\n",
+      "  - low                             : 0.0\n",
+      "  - medium                          : 1.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 4360\n",
+      "  - low                             : 0.1494222222222222\n",
+      "  - medium                          : 0.41739130434782606\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[low]                                       : 0.1494222222222222\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.41739130434782606\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[low]                                       : 0.1494222222222222\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.1494222222222222\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.1494222222222222\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[medium]                                    : 0.41739130434782606\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.41739130434782606\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.41739130434782606\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 1.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.1494222222222222\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.41739130434782606\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 4041539.383618494\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.41739130434782606\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 1.0\n",
+      "  - low                             : 0.7777777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1440\n",
+      "  - low                             : 0.8848\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[low]                                       : 0.8848\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.7777777777777778\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.7777777777777778\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.7777777777777778\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[low]                                       : 0.8848\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.8848\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 815102.9227350706\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.7777777777777778\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: bathrooms               = 2.25\n",
+      "  - low                             : 0.125\n",
+      "  - medium                          : 0.625\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: sqft_living             = 1960\n",
+      "  - low                             : 0.7865777777777778\n",
+      "  - medium                          : 0.0\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF bathrooms[low] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[low]                                       : 0.7865777777777778\n",
+      "                       bathrooms[low] AND sqft_living[low] = 0.125\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.125\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF bathrooms[low] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                    bathrooms[low] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF bathrooms[low] AND sqft_living[high] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[low]                                         : 0.125\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                      bathrooms[low] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF bathrooms[medium] AND sqft_living[low] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[low]                                       : 0.7865777777777778\n",
+      "                    bathrooms[medium] AND sqft_living[low] = 0.625\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.625\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF bathrooms[medium] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                 bathrooms[medium] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF bathrooms[medium] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[medium]                                      : 0.625\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                   bathrooms[medium] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF bathrooms[high] AND sqft_living[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[low]                                       : 0.7865777777777778\n",
+      "                      bathrooms[high] AND sqft_living[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF bathrooms[high] AND sqft_living[medium] THEN price[medium]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[medium]                                    : 0.0\n",
+      "                   bathrooms[high] AND sqft_living[medium] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                             price[medium] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF bathrooms[high] AND sqft_living[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - bathrooms[high]                                        : 0.0\n",
+      "  - sqft_living[high]                                      : 0.0\n",
+      "                     bathrooms[high] AND sqft_living[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 3776812.006111908\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.125\n",
+      "  medium:\n",
+      "    Accumulate using accumulation_max : 0.625\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "\n",
+      "    bathrooms  sqft_living      price  Predicted Price\n",
+      "14       1.00         1140   160000.0     8.151029e+05\n",
+      "12       1.00         1410   175000.0     8.151029e+05\n",
+      "5        2.00         1710   211000.0     3.573309e+06\n",
+      "18       1.00         1440   355000.0     8.151029e+05\n",
+      "13       2.25         1960   365000.0     3.776812e+06\n",
+      "0        2.25         2070   365000.0     3.776812e+06\n",
+      "8        2.50         1600   384500.0     3.901451e+06\n",
+      "11       1.75         1930   385000.0     3.287220e+06\n",
+      "19       2.25         1960   474000.0     3.776812e+06\n",
+      "9        1.00          910   605000.0     8.151029e+05\n",
+      "10       1.00         1830   638000.0     8.151029e+05\n",
+      "7        2.50         1800   680000.0     3.901451e+06\n",
+      "4        2.50         2550   711000.0     3.898895e+06\n",
+      "6        2.50         2690   790000.0     3.898624e+06\n",
+      "17       3.25         4360   795127.0     4.041539e+06\n",
+      "16       1.00         1430   800000.0     8.151029e+05\n",
+      "1        3.00         2900   865000.0     4.012046e+06\n",
+      "2        2.50         3770  1038000.0     3.898018e+06\n",
+      "15       3.75         4130  1070000.0     4.075260e+06\n",
+      "3        3.50         4560  1490000.0     4.017677e+06\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Берём случайно записи из фрейма\n",
+    "df_random = df_house[['bathrooms', 'sqft_living', 'price']].sample(20, random_state=42)\n",
+    "df_random = df_random.reset_index(drop=True)\n",
+    "\n",
+    "\n",
+    "predicted_prices = []\n",
+    "\n",
+    "for i in range(len(df_random)):\n",
+    "    prices.input['bathrooms'] = df_random.loc[i, 'bathrooms']\n",
+    "    prices.input['sqft_living'] = df_random.loc[i, 'sqft_living']\n",
+    "    prices.compute()\n",
+    "    a = prices.print_state()\n",
+    "    predicted_prices.append(prices.output['price'])\n",
+    "\n",
+    "\n",
+    "df_random['Predicted Price'] = predicted_prices\n",
+    "df_random_sorted = df_random.sort_values(by='price')\n",
+    "\n",
+    "\n",
+    "# Вывод результатов\n",
+    "print(df_random_sorted[['bathrooms', 'sqft_living', 'price', 'Predicted Price']])\n",
+    "\n",
+    "# Визуализация графиком\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "plt.plot(df_random.index, df_random_sorted['price'], marker='o', label='Real Price', color='red')\n",
+    "plt.plot(df_random.index, df_random_sorted['Predicted Price'], marker='s', label='Predicted Price', color='green')\n",
+    "plt.xlabel(\"Index\")\n",
+    "plt.ylabel(\"Price\")\n",
+    "plt.legend()\n",
+    "plt.title(\"Сравнение реальных цен с предсказанными\")\n",
+    "plt.show()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Вывод... вывод не утешительный, заааачеем ради чегооо...  \n",
+    "\n",
+    "Система позорно предсказывает цену, по входным характеристикам. Она практически не может предсказать ни маленькую, ни большую цену.  \n",
+    "\n",
+    "Как-то так ^_^"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "mai",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/laboratory_7/requirements.txt b/laboratory_7/requirements.txt
new file mode 100644
index 0000000..5f04788
--- /dev/null
+++ b/laboratory_7/requirements.txt
@@ -0,0 +1,40 @@
+asttokens==2.4.1
+colorama==0.4.6
+comm==0.2.2
+contourpy==1.3.0
+cycler==0.12.1
+debugpy==1.8.5
+decorator==5.1.1
+executing==2.1.0
+fonttools==4.53.1
+ipykernel==6.29.5
+ipython==8.27.0
+jedi==0.19.1
+jupyter_client==8.6.3
+jupyter_core==5.7.2
+kiwisolver==1.4.7
+matplotlib==3.9.2
+matplotlib-inline==0.1.7
+nest-asyncio==1.6.0
+numpy==2.1.1
+packaging==24.1
+pandas==2.2.2
+parso==0.8.4
+pillow==10.4.0
+platformdirs==4.3.6
+prompt_toolkit==3.0.47
+psutil==6.0.0
+pure_eval==0.2.3
+Pygments==2.18.0
+pyparsing==3.1.4
+python-dateutil==2.9.0.post0
+pytz==2024.2
+pywin32==306
+pyzmq==26.2.0
+seaborn==0.13.2
+six==1.16.0
+stack-data==0.6.3
+tornado==6.4.1
+traitlets==5.14.3
+tzdata==2024.1
+wcwidth==0.2.13