From 73dcecaad98b9f1f2458c7d547ac5654c0f055eb Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=9C=D0=B0=D0=BA=D1=81=D0=B8=D0=BC=20=D0=AF=D0=BA=D0=BE?=
 =?UTF-8?q?=D0=B2=D0=BB=D0=B5=D0=B2?= <shotboll16@gmail.com>
Date: Fri, 15 Nov 2024 17:35:10 +0400
Subject: [PATCH] =?UTF-8?q?=D1=8F=20=D0=BF=D1=80=D0=BE=D0=BA=D0=BB=D0=B8?=
 =?UTF-8?q?=D0=BD=D0=B0=D1=8E=20=D1=8D=D1=82=D1=83=20=D0=BE=D1=88=D0=B8?=
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Content-Transfer-Encoding: 8bit

---
 lab_4/lab_4.ipynb | 1018 +++++++++++++++++++++++++++++++--------------
 1 file changed, 700 insertions(+), 318 deletions(-)

diff --git a/lab_4/lab_4.ipynb b/lab_4/lab_4.ipynb
index 6838ed8..b1c86bc 100644
--- a/lab_4/lab_4.ipynb
+++ b/lab_4/lab_4.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 313,
    "metadata": {},
    "outputs": [
     {
@@ -375,7 +375,7 @@
        "[10000 rows x 21 columns]"
       ]
      },
-     "execution_count": 112,
+     "execution_count": 313,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -401,7 +401,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 113,
+   "execution_count": 314,
    "metadata": {},
    "outputs": [
     {
@@ -1026,7 +1026,7 @@
        "[20 rows x 22 columns]"
       ]
      },
-     "execution_count": 113,
+     "execution_count": 314,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1062,7 +1062,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 114,
+   "execution_count": 315,
    "metadata": {},
    "outputs": [
     {
@@ -2103,8 +2103,6 @@
     "\n",
     "features_preprocessing -- трансформер для предобработки признаков\n",
     "\n",
-    "features_engineering -- трансформер для конструирования признаков\n",
-    "\n",
     "drop_columns -- трансформер для удаления колонок\n",
     "\n",
     "pipeline_end -- основной конвейер предобработки данных и конструирования признаков"
@@ -2112,7 +2110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 191,
+   "execution_count": 316,
    "metadata": {},
    "outputs": [
     {
@@ -2146,309 +2144,576 @@
        "      <th>condition</th>\n",
        "      <th>grade</th>\n",
        "      <th>sqft_above</th>\n",
-       "      <th>sqft_basement</th>\n",
-       "      <th>yr_built</th>\n",
+       "      <th>...</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",
-       "      <th>price_category</th>\n",
+       "      <th>price_h</th>\n",
+       "      <th>price_l</th>\n",
+       "      <th>price_m</th>\n",
+       "      <th>price_vh</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>3</td>\n",
-       "      <td>3260000340</td>\n",
-       "      <td>732600.0</td>\n",
-       "      <td>4</td>\n",
-       "      <td>2.5</td>\n",
-       "      <td>2130</td>\n",
-       "      <td>7300</td>\n",
+       "      <td>-0.451103</td>\n",
+       "      <td>0.916381</td>\n",
+       "      <td>0.700559</td>\n",
+       "      <td>0.573416</td>\n",
+       "      <td>0.081706</td>\n",
+       "      <td>-0.187493</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>0.839159</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>-0.638064</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-1.349962</td>\n",
+       "      <td>0.32254</td>\n",
+       "      <td>0.340593</td>\n",
+       "      <td>0.223199</td>\n",
+       "      <td>-0.210584</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>4</td>\n",
-       "      <td>7</td>\n",
-       "      <td>1230</td>\n",
-       "      <td>900</td>\n",
-       "      <td>1963</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98005</td>\n",
-       "      <td>47.605</td>\n",
-       "      <td>-122.167</td>\n",
-       "      <td>2130</td>\n",
-       "      <td>7560</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
-       "      <td>2</td>\n",
-       "      <td>9828702055</td>\n",
-       "      <td>358000.0</td>\n",
-       "      <td>2</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>960</td>\n",
-       "      <td>1808</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>7</td>\n",
-       "      <td>960</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1993</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98122</td>\n",
-       "      <td>47.6183</td>\n",
-       "      <td>-122.298</td>\n",
-       "      <td>1290</td>\n",
-       "      <td>1668</td>\n",
+       "      <td>1.845014</td>\n",
+       "      <td>-0.589326</td>\n",
+       "      <td>-1.49426</td>\n",
+       "      <td>-0.72971</td>\n",
+       "      <td>-1.191326</td>\n",
+       "      <td>-0.302999</td>\n",
+       "      <td>1.120073</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>-0.969739</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>0.820656</td>\n",
+       "      <td>0.417588</td>\n",
+       "      <td>-0.601419</td>\n",
+       "      <td>-1.022503</td>\n",
+       "      <td>-0.421966</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
-       "      <td>1</td>\n",
-       "      <td>3438500625</td>\n",
-       "      <td>210000.0</td>\n",
-       "      <td>3</td>\n",
+       "      <td>-0.388708</td>\n",
+       "      <td>-1.184213</td>\n",
+       "      <td>-0.396851</td>\n",
+       "      <td>-1.381273</td>\n",
+       "      <td>-1.060759</td>\n",
+       "      <td>0.101544</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>-1.369558</td>\n",
+       "      <td>-0.822328</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>0.523819</td>\n",
+       "      <td>-0.059795</td>\n",
+       "      <td>-1.025683</td>\n",
+       "      <td>-0.889035</td>\n",
+       "      <td>-0.208431</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>1080</td>\n",
-       "      <td>21043</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>6</td>\n",
-       "      <td>1080</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1942</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98106</td>\n",
-       "      <td>47.5515</td>\n",
-       "      <td>-122.357</td>\n",
-       "      <td>1380</td>\n",
-       "      <td>7620</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
-       "      <td>2</td>\n",
-       "      <td>2422029094</td>\n",
-       "      <td>517534.0</td>\n",
-       "      <td>2</td>\n",
+       "      <td>-0.74402</td>\n",
+       "      <td>0.051922</td>\n",
+       "      <td>-1.49426</td>\n",
+       "      <td>-1.381273</td>\n",
+       "      <td>-1.32951</td>\n",
+       "      <td>2.686416</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>-2.22647</td>\n",
+       "      <td>-1.125749</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-0.144063</td>\n",
+       "      <td>-1.221808</td>\n",
+       "      <td>-1.924549</td>\n",
+       "      <td>-0.889035</td>\n",
+       "      <td>4.682444</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>833</td>\n",
-       "      <td>143947</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>5</td>\n",
-       "      <td>833</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2006</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98070</td>\n",
-       "      <td>47.3889</td>\n",
-       "      <td>-122.482</td>\n",
-       "      <td>1380</td>\n",
-       "      <td>143947</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
-       "      <td>2</td>\n",
-       "      <td>7462900015</td>\n",
-       "      <td>387000.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2.25</td>\n",
-       "      <td>1760</td>\n",
-       "      <td>45133</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>7</td>\n",
-       "      <td>1760</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1984</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98065</td>\n",
-       "      <td>47.5124</td>\n",
-       "      <td>-121.866</td>\n",
-       "      <td>1910</td>\n",
-       "      <td>51773</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
+       "      <td>1.018038</td>\n",
+       "      <td>-0.47276</td>\n",
+       "      <td>-0.396851</td>\n",
+       "      <td>0.247635</td>\n",
+       "      <td>-0.320877</td>\n",
+       "      <td>0.608196</td>\n",
+       "      <td>1.120073</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>0.013003</td>\n",
        "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7995</th>\n",
-       "      <td>2</td>\n",
-       "      <td>2787720140</td>\n",
-       "      <td>416000.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2.5</td>\n",
-       "      <td>1790</td>\n",
-       "      <td>11542</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-0.236825</td>\n",
+       "      <td>-0.339221</td>\n",
+       "      <td>2.505062</td>\n",
+       "      <td>-0.103056</td>\n",
+       "      <td>1.375604</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>5</td>\n",
-       "      <td>7</td>\n",
-       "      <td>1190</td>\n",
-       "      <td>600</td>\n",
-       "      <td>1969</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98059</td>\n",
-       "      <td>47.5124</td>\n",
-       "      <td>-122.16</td>\n",
-       "      <td>1790</td>\n",
-       "      <td>9131</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7996</th>\n",
-       "      <td>3</td>\n",
-       "      <td>6192400400</td>\n",
-       "      <td>775000.0</td>\n",
-       "      <td>4</td>\n",
-       "      <td>2.5</td>\n",
-       "      <td>3090</td>\n",
-       "      <td>7112</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>9</td>\n",
-       "      <td>3090</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2001</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98052</td>\n",
-       "      <td>47.705</td>\n",
-       "      <td>-122.118</td>\n",
-       "      <td>3050</td>\n",
-       "      <td>6000</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7997</th>\n",
-       "      <td>2</td>\n",
-       "      <td>2296500036</td>\n",
-       "      <td>450000.0</td>\n",
-       "      <td>4</td>\n",
-       "      <td>2.75</td>\n",
-       "      <td>2980</td>\n",
-       "      <td>13260</td>\n",
+       "      <th>5</th>\n",
+       "      <td>-0.083826</td>\n",
+       "      <td>-0.492858</td>\n",
+       "      <td>-0.396851</td>\n",
+       "      <td>1.550761</td>\n",
+       "      <td>-0.701698</td>\n",
+       "      <td>-0.314672</td>\n",
+       "      <td>3.078884</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>0.344264</td>\n",
+       "      <td>-0.416947</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>0.468162</td>\n",
+       "      <td>0.987875</td>\n",
+       "      <td>-0.903438</td>\n",
+       "      <td>-0.844546</td>\n",
+       "      <td>-0.436854</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>4</td>\n",
-       "      <td>8</td>\n",
-       "      <td>1800</td>\n",
-       "      <td>1180</td>\n",
-       "      <td>1979</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98056</td>\n",
-       "      <td>47.5152</td>\n",
-       "      <td>-122.197</td>\n",
-       "      <td>1920</td>\n",
-       "      <td>10731</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7998</th>\n",
-       "      <td>1</td>\n",
-       "      <td>2787310130</td>\n",
-       "      <td>289950.0</td>\n",
-       "      <td>4</td>\n",
-       "      <td>1.75</td>\n",
-       "      <td>2090</td>\n",
-       "      <td>7416</td>\n",
+       "      <th>6</th>\n",
+       "      <td>0.301277</td>\n",
+       "      <td>-0.953091</td>\n",
+       "      <td>-0.396851</td>\n",
+       "      <td>0.573416</td>\n",
+       "      <td>-0.712579</td>\n",
+       "      <td>-0.180574</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>-0.773191</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-0.886155</td>\n",
+       "      <td>-1.293987</td>\n",
+       "      <td>0.254302</td>\n",
+       "      <td>-0.666588</td>\n",
+       "      <td>-0.205992</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>4</td>\n",
-       "      <td>7</td>\n",
-       "      <td>1050</td>\n",
-       "      <td>1040</td>\n",
-       "      <td>1970</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98031</td>\n",
-       "      <td>47.4107</td>\n",
-       "      <td>-122.179</td>\n",
-       "      <td>1710</td>\n",
-       "      <td>7527</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>7999</th>\n",
-       "      <td>2</td>\n",
-       "      <td>8567300110</td>\n",
-       "      <td>485000.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>2.5</td>\n",
-       "      <td>2340</td>\n",
-       "      <td>59058</td>\n",
+       "      <th>7</th>\n",
+       "      <td>-0.086798</td>\n",
+       "      <td>-1.148038</td>\n",
+       "      <td>-1.49426</td>\n",
+       "      <td>-1.381273</td>\n",
+       "      <td>-1.25661</td>\n",
+       "      <td>-0.232501</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>-1.369558</td>\n",
+       "      <td>-1.043445</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>0.523819</td>\n",
+       "      <td>-0.249176</td>\n",
+       "      <td>-1.018493</td>\n",
+       "      <td>-1.600865</td>\n",
+       "      <td>-0.296686</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>1.0</td>\n",
-       "      <td>3</td>\n",
-       "      <td>8</td>\n",
-       "      <td>2340</td>\n",
-       "      <td>0</td>\n",
-       "      <td>1985</td>\n",
-       "      <td>0</td>\n",
-       "      <td>98038</td>\n",
-       "      <td>47.4052</td>\n",
-       "      <td>-122.028</td>\n",
-       "      <td>2700</td>\n",
-       "      <td>37263</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>-0.824567</td>\n",
+       "      <td>-1.148038</td>\n",
+       "      <td>-1.49426</td>\n",
+       "      <td>-1.381273</td>\n",
+       "      <td>-1.0934</td>\n",
+       "      <td>-0.15174</td>\n",
+       "      <td>0.140667</td>\n",
+       "      <td>0.839159</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>-0.859181</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-1.387066</td>\n",
+       "      <td>-1.937882</td>\n",
+       "      <td>-0.60861</td>\n",
+       "      <td>-0.636929</td>\n",
+       "      <td>-0.137397</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>1.647935</td>\n",
+       "      <td>-0.762165</td>\n",
+       "      <td>2.895378</td>\n",
+       "      <td>0.899198</td>\n",
+       "      <td>0.963036</td>\n",
+       "      <td>-0.186442</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>0.344264</td>\n",
+       "      <td>0.037571</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-1.016021</td>\n",
+       "      <td>-1.783519</td>\n",
+       "      <td>-0.896247</td>\n",
+       "      <td>0.208369</td>\n",
+       "      <td>-0.186332</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>-1.159614</td>\n",
+       "      <td>-0.581287</td>\n",
+       "      <td>-1.49426</td>\n",
+       "      <td>-1.381273</td>\n",
+       "      <td>-1.321893</td>\n",
+       "      <td>-0.185096</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>0.839159</td>\n",
+       "      <td>-1.369558</td>\n",
+       "      <td>-1.11715</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-0.830498</td>\n",
+       "      <td>0.837799</td>\n",
+       "      <td>0.304638</td>\n",
+       "      <td>-0.355163</td>\n",
+       "      <td>-0.130796</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>-1.329183</td>\n",
+       "      <td>-0.681775</td>\n",
+       "      <td>-1.49426</td>\n",
+       "      <td>-1.381273</td>\n",
+       "      <td>-1.071639</td>\n",
+       "      <td>-0.200575</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>0.839159</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>-0.834612</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>1.024731</td>\n",
+       "      <td>1.226566</td>\n",
+       "      <td>-1.025683</td>\n",
+       "      <td>-0.444141</td>\n",
+       "      <td>-0.202404</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>0.377864</td>\n",
+       "      <td>0.286926</td>\n",
+       "      <td>0.700559</td>\n",
+       "      <td>0.573416</td>\n",
+       "      <td>0.419005</td>\n",
+       "      <td>0.256379</td>\n",
+       "      <td>1.120073</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>0.344264</td>\n",
+       "      <td>0.848334</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-0.923259</td>\n",
+       "      <td>1.277306</td>\n",
+       "      <td>-0.169963</td>\n",
+       "      <td>0.742242</td>\n",
+       "      <td>-0.071779</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>0.289882</td>\n",
+       "      <td>-0.88677</td>\n",
+       "      <td>-0.396851</td>\n",
+       "      <td>0.573416</td>\n",
+       "      <td>0.103467</td>\n",
+       "      <td>-0.143853</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>0.344264</td>\n",
+       "      <td>-0.244967</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>2.045107</td>\n",
+       "      <td>-0.729417</td>\n",
+       "      <td>-0.428836</td>\n",
+       "      <td>-0.043737</td>\n",
+       "      <td>-0.155335</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>1.613049</td>\n",
+       "      <td>0.282907</td>\n",
+       "      <td>-0.396851</td>\n",
+       "      <td>-0.078147</td>\n",
+       "      <td>0.103467</td>\n",
+       "      <td>-0.259422</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>0.344264</td>\n",
+       "      <td>-0.822328</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>0.727894</td>\n",
+       "      <td>0.868529</td>\n",
+       "      <td>-1.277366</td>\n",
+       "      <td>0.223199</td>\n",
+       "      <td>-0.338303</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>-0.962885</td>\n",
+       "      <td>0.285118</td>\n",
+       "      <td>0.700559</td>\n",
+       "      <td>0.573416</td>\n",
+       "      <td>0.005542</td>\n",
+       "      <td>-0.183813</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>0.344264</td>\n",
+       "      <td>-0.380094</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-0.478004</td>\n",
+       "      <td>1.195837</td>\n",
+       "      <td>0.78643</td>\n",
+       "      <td>0.445646</td>\n",
+       "      <td>-0.180592</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>1.722145</td>\n",
+       "      <td>-0.259726</td>\n",
+       "      <td>-0.396851</td>\n",
+       "      <td>-0.403928</td>\n",
+       "      <td>-0.571131</td>\n",
+       "      <td>-0.18865</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>0.839159</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>-0.269535</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-0.811945</td>\n",
+       "      <td>1.222993</td>\n",
+       "      <td>0.168011</td>\n",
+       "      <td>-0.666588</td>\n",
+       "      <td>-0.213095</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>0.740562</td>\n",
+       "      <td>1.589247</td>\n",
+       "      <td>0.700559</td>\n",
+       "      <td>1.550761</td>\n",
+       "      <td>2.878025</td>\n",
+       "      <td>0.466843</td>\n",
+       "      <td>1.120073</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>2.058087</td>\n",
+       "      <td>2.052192</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>-1.349962</td>\n",
+       "      <td>0.604825</td>\n",
+       "      <td>0.340593</td>\n",
+       "      <td>2.462498</td>\n",
+       "      <td>0.79434</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>-1.555659</td>\n",
+       "      <td>-0.922945</td>\n",
+       "      <td>-0.396851</td>\n",
+       "      <td>-1.381273</td>\n",
+       "      <td>-0.799624</td>\n",
+       "      <td>-0.107784</td>\n",
+       "      <td>-0.838739</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>-0.527505</td>\n",
+       "      <td>...</td>\n",
+       "      <td>-0.2158</td>\n",
+       "      <td>1.432881</td>\n",
+       "      <td>1.536008</td>\n",
+       "      <td>-0.644564</td>\n",
+       "      <td>-0.978014</td>\n",
+       "      <td>-0.183354</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>-0.953738</td>\n",
+       "      <td>0.142224</td>\n",
+       "      <td>2.895378</td>\n",
+       "      <td>1.224979</td>\n",
+       "      <td>0.886872</td>\n",
+       "      <td>4.00146</td>\n",
+       "      <td>1.120073</td>\n",
+       "      <td>-0.666734</td>\n",
+       "      <td>-0.512647</td>\n",
+       "      <td>0.713207</td>\n",
+       "      <td>...</td>\n",
+       "      <td>4.605736</td>\n",
+       "      <td>-0.663527</td>\n",
+       "      <td>-1.135335</td>\n",
+       "      <td>0.85834</td>\n",
+       "      <td>0.593944</td>\n",
+       "      <td>1.659169</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>8000 rows × 19 columns</p>\n",
+       "<p>20 rows × 22 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "     id       price  bedrooms bathrooms sqft_living sqft_lot  floors  \\\n",
-       "0     3  3260000340  732600.0         4         2.5     2130    7300   \n",
-       "1     2  9828702055  358000.0         2         1.5      960    1808   \n",
-       "2     1  3438500625  210000.0         3         1.0     1080   21043   \n",
-       "3     2  2422029094  517534.0         2         1.0      833  143947   \n",
-       "4     2  7462900015  387000.0         3        2.25     1760   45133   \n",
-       "...  ..         ...       ...       ...         ...      ...     ...   \n",
-       "7995  2  2787720140  416000.0         3         2.5     1790   11542   \n",
-       "7996  3  6192400400  775000.0         4         2.5     3090    7112   \n",
-       "7997  2  2296500036  450000.0         4        2.75     2980   13260   \n",
-       "7998  1  2787310130  289950.0         4        1.75     2090    7416   \n",
-       "7999  2  8567300110  485000.0         3         2.5     2340   59058   \n",
+       "          id     price  bedrooms bathrooms sqft_living  sqft_lot    floors  \\\n",
+       "0  -0.451103  0.916381  0.700559  0.573416    0.081706 -0.187493 -0.838739   \n",
+       "1   1.845014 -0.589326  -1.49426  -0.72971   -1.191326 -0.302999  1.120073   \n",
+       "2  -0.388708 -1.184213 -0.396851 -1.381273   -1.060759  0.101544 -0.838739   \n",
+       "3   -0.74402  0.051922  -1.49426 -1.381273    -1.32951  2.686416 -0.838739   \n",
+       "4   1.018038  -0.47276 -0.396851  0.247635   -0.320877  0.608196  1.120073   \n",
+       "5  -0.083826 -0.492858 -0.396851  1.550761   -0.701698 -0.314672  3.078884   \n",
+       "6   0.301277 -0.953091 -0.396851  0.573416   -0.712579 -0.180574 -0.838739   \n",
+       "7  -0.086798 -1.148038  -1.49426 -1.381273    -1.25661 -0.232501 -0.838739   \n",
+       "8  -0.824567 -1.148038  -1.49426 -1.381273     -1.0934  -0.15174  0.140667   \n",
+       "9   1.647935 -0.762165  2.895378  0.899198    0.963036 -0.186442 -0.838739   \n",
+       "10 -1.159614 -0.581287  -1.49426 -1.381273   -1.321893 -0.185096 -0.838739   \n",
+       "11 -1.329183 -0.681775  -1.49426 -1.381273   -1.071639 -0.200575 -0.838739   \n",
+       "12  0.377864  0.286926  0.700559  0.573416    0.419005  0.256379  1.120073   \n",
+       "13  0.289882  -0.88677 -0.396851  0.573416    0.103467 -0.143853 -0.838739   \n",
+       "14  1.613049  0.282907 -0.396851 -0.078147    0.103467 -0.259422 -0.838739   \n",
+       "15 -0.962885  0.285118  0.700559  0.573416    0.005542 -0.183813 -0.838739   \n",
+       "16  1.722145 -0.259726 -0.396851 -0.403928   -0.571131  -0.18865 -0.838739   \n",
+       "17  0.740562  1.589247  0.700559  1.550761    2.878025  0.466843  1.120073   \n",
+       "18 -1.555659 -0.922945 -0.396851 -1.381273   -0.799624 -0.107784 -0.838739   \n",
+       "19 -0.953738  0.142224  2.895378  1.224979    0.886872   4.00146  1.120073   \n",
        "\n",
-       "     condition grade sqft_above sqft_basement yr_built yr_renovated zipcode  \\\n",
-       "0          1.0     4          7          1230      900         1963       0   \n",
-       "1          2.0     3          7           960        0         1993       0   \n",
-       "2          1.0     3          6          1080        0         1942       0   \n",
-       "3          1.0     3          5           833        0         2006       0   \n",
-       "4          2.0     3          7          1760        0         1984       0   \n",
-       "...        ...   ...        ...           ...      ...          ...     ...   \n",
-       "7995       1.0     5          7          1190      600         1969       0   \n",
-       "7996       2.0     3          9          3090        0         2001       0   \n",
-       "7997       1.0     4          8          1800     1180         1979       0   \n",
-       "7998       1.0     4          7          1050     1040         1970       0   \n",
-       "7999       1.0     3          8          2340        0         1985       0   \n",
+       "   condition     grade sqft_above  ... yr_renovated   zipcode       lat  \\\n",
+       "0   0.839159 -0.512647  -0.638064  ...      -0.2158 -1.349962   0.32254   \n",
+       "1  -0.666734 -0.512647  -0.969739  ...      -0.2158  0.820656  0.417588   \n",
+       "2  -0.666734 -1.369558  -0.822328  ...      -0.2158  0.523819 -0.059795   \n",
+       "3  -0.666734  -2.22647  -1.125749  ...      -0.2158 -0.144063 -1.221808   \n",
+       "4  -0.666734 -0.512647   0.013003  ...      -0.2158 -0.236825 -0.339221   \n",
+       "5  -0.666734  0.344264  -0.416947  ...      -0.2158  0.468162  0.987875   \n",
+       "6  -0.666734 -0.512647  -0.773191  ...      -0.2158 -0.886155 -1.293987   \n",
+       "7  -0.666734 -1.369558  -1.043445  ...      -0.2158  0.523819 -0.249176   \n",
+       "8   0.839159 -0.512647  -0.859181  ...      -0.2158 -1.387066 -1.937882   \n",
+       "9  -0.666734  0.344264   0.037571  ...      -0.2158 -1.016021 -1.783519   \n",
+       "10  0.839159 -1.369558   -1.11715  ...      -0.2158 -0.830498  0.837799   \n",
+       "11  0.839159 -0.512647  -0.834612  ...      -0.2158  1.024731  1.226566   \n",
+       "12 -0.666734  0.344264   0.848334  ...      -0.2158 -0.923259  1.277306   \n",
+       "13 -0.666734  0.344264  -0.244967  ...      -0.2158  2.045107 -0.729417   \n",
+       "14 -0.666734  0.344264  -0.822328  ...      -0.2158  0.727894  0.868529   \n",
+       "15 -0.666734  0.344264  -0.380094  ...      -0.2158 -0.478004  1.195837   \n",
+       "16  0.839159 -0.512647  -0.269535  ...      -0.2158 -0.811945  1.222993   \n",
+       "17 -0.666734  2.058087   2.052192  ...      -0.2158 -1.349962  0.604825   \n",
+       "18 -0.666734 -0.512647  -0.527505  ...      -0.2158  1.432881  1.536008   \n",
+       "19 -0.666734 -0.512647   0.713207  ...     4.605736 -0.663527 -1.135335   \n",
        "\n",
-       "        lat     long sqft_living15 sqft_lot15 price_category  \n",
-       "0     98005   47.605      -122.167       2130           7560  \n",
-       "1     98122  47.6183      -122.298       1290           1668  \n",
-       "2     98106  47.5515      -122.357       1380           7620  \n",
-       "3     98070  47.3889      -122.482       1380         143947  \n",
-       "4     98065  47.5124      -121.866       1910          51773  \n",
-       "...     ...      ...           ...        ...            ...  \n",
-       "7995  98059  47.5124       -122.16       1790           9131  \n",
-       "7996  98052   47.705      -122.118       3050           6000  \n",
-       "7997  98056  47.5152      -122.197       1920          10731  \n",
-       "7998  98031  47.4107      -122.179       1710           7527  \n",
-       "7999  98038  47.4052      -122.028       2700          37263  \n",
+       "        long sqft_living15 sqft_lot15 price_h price_l price_m price_vh  \n",
+       "0   0.340593      0.223199  -0.210584     1.0     0.0     0.0      0.0  \n",
+       "1  -0.601419     -1.022503  -0.421966     0.0     0.0     1.0      0.0  \n",
+       "2  -1.025683     -0.889035  -0.208431     0.0     1.0     0.0      0.0  \n",
+       "3  -1.924549     -0.889035   4.682444     0.0     0.0     1.0      0.0  \n",
+       "4   2.505062     -0.103056   1.375604     0.0     0.0     1.0      0.0  \n",
+       "5  -0.903438     -0.844546  -0.436854     0.0     0.0     1.0      0.0  \n",
+       "6   0.254302     -0.666588  -0.205992     0.0     1.0     0.0      0.0  \n",
+       "7  -1.018493     -1.600865  -0.296686     0.0     1.0     0.0      0.0  \n",
+       "8   -0.60861     -0.636929  -0.137397     0.0     1.0     0.0      0.0  \n",
+       "9  -0.896247      0.208369  -0.186332     0.0     1.0     0.0      0.0  \n",
+       "10  0.304638     -0.355163  -0.130796     0.0     0.0     1.0      0.0  \n",
+       "11 -1.025683     -0.444141  -0.202404     0.0     1.0     0.0      0.0  \n",
+       "12 -0.169963      0.742242  -0.071779     0.0     0.0     1.0      0.0  \n",
+       "13 -0.428836     -0.043737  -0.155335     0.0     1.0     0.0      0.0  \n",
+       "14 -1.277366      0.223199  -0.338303     0.0     0.0     1.0      0.0  \n",
+       "15   0.78643      0.445646  -0.180592     0.0     0.0     1.0      0.0  \n",
+       "16  0.168011     -0.666588  -0.213095     0.0     0.0     1.0      0.0  \n",
+       "17  0.340593      2.462498    0.79434     0.0     0.0     0.0      1.0  \n",
+       "18 -0.644564     -0.978014  -0.183354     0.0     1.0     0.0      0.0  \n",
+       "19   0.85834      0.593944   1.659169     0.0     0.0     1.0      0.0  \n",
        "\n",
-       "[8000 rows x 19 columns]"
+       "[20 rows x 22 columns]"
       ]
      },
-     "execution_count": 191,
+     "execution_count": 316,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2465,34 +2730,7 @@
     "from sklearn.model_selection import train_test_split\n",
     "from sklearn.pipeline import make_pipeline\n",
     "\n",
-    "class HousesFeatures(BaseEstimator, TransformerMixin):\n",
-    "    def __init__(self):\n",
-    "        pass\n",
-    "\n",
-    "    def fit(self, X, y=None):\n",
-    "        return self\n",
-    "\n",
-    "\n",
-    "    def transform(self, X, y=None):\n",
-    "\n",
-    "        def get_price_type(category) -> int:\n",
-    "            if pd.isna(category):\n",
-    "                return \"unknown\"\n",
-    "            if category == 'low':\n",
-    "                return 1\n",
-    "            elif category == 'middle':\n",
-    "                return 2\n",
-    "            elif category == 'high':\n",
-    "                return 3\n",
-    "            elif category == 'very_high':\n",
-    "                return 4\n",
-    "\n",
-    "        # Преобразование категориальных столбцов в числовые 1/0\n",
-    "        X[\"price_category\"] = [get_price_type(category) for category in X[\"price_category\"]]\n",
-    "        return X\n",
-    "\n",
-    "    def get_feature_names_out(self, features_in):\n",
-    "        return np.append(features_in, [\"price_type\"], axis=0)\n",
+    "random_state = 42\n",
     "\n",
     "# Указываем столбцы, которые нужно удалить и обрабатывать\n",
     "columns_to_drop = [\"date\", \"view\", \"waterfront\"]\n",
@@ -2518,8 +2756,8 @@
     ")\n",
     "\n",
     "# Определяем предобработку для категориальных данных\n",
-    "cat_imputer = SimpleImputer(strategy=\"constant\", fill_value=\"unknown\")\n",
-    "cat_encoder = OneHotEncoder(handle_unknown=\"ignore\", sparse_output=False, drop=\"first\")\n",
+    "cat_imputer = SimpleImputer(strategy=\"constant\")\n",
+    "cat_encoder = OneHotEncoder(handle_unknown=\"ignore\", sparse_output=False)\n",
     "preprocessing_cat = Pipeline(\n",
     "    [\n",
     "        (\"imputer\", cat_imputer),\n",
@@ -2532,19 +2770,11 @@
     "    transformers=[\n",
     "        (\"prepocessing_num\", preprocessing_num, num_columns),\n",
     "        (\"prepocessing_cat\", preprocessing_cat, cat_columns),\n",
-    "        # (\"prepocessing_features\", cat_imputer, [\"price_category\"]),\n",
+    "        (\"prepocessing_features\", cat_imputer, [\"price_category\"]),\n",
     "    ],\n",
     "    remainder=\"passthrough\"\n",
     ")\n",
     "\n",
-    "features_engineering = ColumnTransformer(\n",
-    "    verbose_feature_names_out=False,\n",
-    "    transformers=[\n",
-    "        (\"add_features\", HousesFeatures(), [\"price_category\"]),\n",
-    "    ],\n",
-    "    remainder=\"passthrough\",\n",
-    ")\n",
-    "\n",
     "drop_columns = ColumnTransformer(\n",
     "    verbose_feature_names_out=False,\n",
     "    transformers=[\n",
@@ -2564,29 +2794,181 @@
     "pipeline_end = Pipeline(\n",
     "    [\n",
     "        (\"features_preprocessing\", features_preprocessing),\n",
-    "        (\"features_engineering\", features_engineering),\n",
     "        (\"drop_columns\", drop_columns),\n",
     "        (\"features_postprocessing\", features_postprocessing),\n",
     "    ]\n",
     "\n",
     ")\n",
-    "cols = ['a', 'b']\n",
-    "preprocessing_result = drop_columns.fit_transform(X_train)\n",
-    "preprocessing_result = pd.DataFrame(preprocessing_result, columns=num_columns + cat_columns)\n",
-    "preprocessing_result = features_engineering.fit_transform(preprocessing_result)\n",
-    "preprocessing_result = pd.DataFrame(preprocessing_result, columns=num_columns + cat_columns)\n",
-    "preprocessing_result\n",
-    "# # preprocessing_result = features_preprocessing.fit_transform(preprocessing_result)\n",
-    "# # preprocessing_result = pd.DataFrame(preprocessing_result, columns=num_columns + cat_columns)\n",
+    "cols = ['price_h', 'price_l', 'price_m', 'price_vh']\n",
+    "preprocessing_result = features_preprocessing.fit_transform(X_train)\n",
+    "preprocessing_result = pd.DataFrame(preprocessing_result, columns=num_columns + cat_columns + cols + columns_to_drop)\n",
     "\n",
-    "# preprocessing_result = features_postprocessing.fit_transform(preprocessing_result)\n",
+    "preprocessing_result = drop_columns.fit_transform(preprocessing_result)\n",
+    "preprocessing_result = pd.DataFrame(preprocessing_result, columns=num_columns + cols + cat_columns)\n",
     "\n",
-    "# preprocessing_result = pipeline_end.fit_transform(X_train)\n",
-    "# preprocessed_df = pd.DataFrame(\n",
-    "#     preprocessing_result,\n",
-    "#     columns=pipeline_end.get_feature_names_out(),\n",
-    "# )\n",
-    "# preprocessed_df"
+    "preprocessing_result = preprocessing_result.drop(columns=[\"price_category\"])\n",
+    "preprocessing_result.head(20)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Формирование набора моделей для классификации¶\n",
+    "logistic -- логистическая регрессия\n",
+    "\n",
+    "ridge -- гребневая регрессия\n",
+    "\n",
+    "decision_tree -- дерево решений\n",
+    "\n",
+    "knn -- k-ближайших соседей\n",
+    "\n",
+    "naive_bayes -- наивный Байесовский классификатор\n",
+    "\n",
+    "gradient_boosting -- метод градиентного бустинга (набор деревьев решений)\n",
+    "\n",
+    "random_forest -- метод случайного леса (набор деревьев решений)\n",
+    "\n",
+    "mlp -- многослойный персептрон (нейронная сеть)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 317,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from sklearn import ensemble, linear_model, naive_bayes, neighbors, neural_network, tree\n",
+    "\n",
+    "class_models = {\n",
+    "    \"logistic\": {\"model\": linear_model.LogisticRegression()},\n",
+    "    # \"ridge\": {\"model\": linear_model.RidgeClassifierCV(cv=5, class_weight=\"balanced\")},\n",
+    "    \"ridge\": {\"model\": linear_model.LogisticRegression(penalty=\"l2\", class_weight=\"balanced\")},\n",
+    "    \"decision_tree\": {\n",
+    "        \"model\": tree.DecisionTreeClassifier(max_depth=7, random_state=random_state)\n",
+    "    },\n",
+    "    \"knn\": {\"model\": neighbors.KNeighborsClassifier(n_neighbors=7)},\n",
+    "    \"naive_bayes\": {\"model\": naive_bayes.GaussianNB()},\n",
+    "    \"gradient_boosting\": {\n",
+    "        \"model\": ensemble.GradientBoostingClassifier(n_estimators=210)\n",
+    "    },\n",
+    "    \"random_forest\": {\n",
+    "        \"model\": ensemble.RandomForestClassifier(\n",
+    "            max_depth=11, class_weight=\"balanced\", random_state=random_state\n",
+    "        )\n",
+    "    },\n",
+    "    \"mlp\": {\n",
+    "        \"model\": neural_network.MLPClassifier(\n",
+    "            hidden_layer_sizes=(7,),\n",
+    "            max_iter=500,\n",
+    "            early_stopping=True,\n",
+    "            random_state=random_state,\n",
+    "        )\n",
+    "    },\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Обучение моделей на обучающем наборе данных и оценка на тестовом"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 320,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model: logistic\n"
+     ]
+    },
+    {
+     "ename": "ValueError",
+     "evalue": "Specifying the columns using strings is only supported for dataframes.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\utils\\_indexing.py:338\u001b[0m, in \u001b[0;36m_get_column_indices\u001b[1;34m(X, key)\u001b[0m\n\u001b[0;32m    337\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m--> 338\u001b[0m     all_columns \u001b[38;5;241m=\u001b[39m \u001b[43mX\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\n\u001b[0;32m    339\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m:\n",
+      "\u001b[1;31mAttributeError\u001b[0m: 'numpy.ndarray' object has no attribute 'columns'",
+      "\nDuring handling of the above exception, another exception occurred:\n",
+      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[1;32mIn[320], line 9\u001b[0m\n\u001b[0;32m      6\u001b[0m model \u001b[38;5;241m=\u001b[39m class_models[model_name][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m      8\u001b[0m model_pipeline \u001b[38;5;241m=\u001b[39m Pipeline([(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpipeline\u001b[39m\u001b[38;5;124m\"\u001b[39m, pipeline_end), (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmodel\u001b[39m\u001b[38;5;124m\"\u001b[39m, model)])\n\u001b[1;32m----> 9\u001b[0m model_pipeline \u001b[38;5;241m=\u001b[39m \u001b[43mmodel_pipeline\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX_train\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my_train\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalues\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mravel\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     11\u001b[0m y_train_predict \u001b[38;5;241m=\u001b[39m model_pipeline\u001b[38;5;241m.\u001b[39mpredict(X_train)\n\u001b[0;32m     12\u001b[0m y_test_probs \u001b[38;5;241m=\u001b[39m model_pipeline\u001b[38;5;241m.\u001b[39mpredict_proba(X_test)[:, \u001b[38;5;241m1\u001b[39m]\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\base.py:1473\u001b[0m, in \u001b[0;36m_fit_context.<locals>.decorator.<locals>.wrapper\u001b[1;34m(estimator, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1466\u001b[0m     estimator\u001b[38;5;241m.\u001b[39m_validate_params()\n\u001b[0;32m   1468\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[0;32m   1469\u001b[0m     skip_parameter_validation\u001b[38;5;241m=\u001b[39m(\n\u001b[0;32m   1470\u001b[0m         prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[0;32m   1471\u001b[0m     )\n\u001b[0;32m   1472\u001b[0m ):\n\u001b[1;32m-> 1473\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfit_method\u001b[49m\u001b[43m(\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\pipeline.py:469\u001b[0m, in \u001b[0;36mPipeline.fit\u001b[1;34m(self, X, y, **params)\u001b[0m\n\u001b[0;32m    426\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Fit the model.\u001b[39;00m\n\u001b[0;32m    427\u001b[0m \n\u001b[0;32m    428\u001b[0m \u001b[38;5;124;03mFit all the transformers one after the other and sequentially transform the\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    466\u001b[0m \u001b[38;5;124;03m    Pipeline with fitted steps.\u001b[39;00m\n\u001b[0;32m    467\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m    468\u001b[0m routed_params \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_method_params(method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfit\u001b[39m\u001b[38;5;124m\"\u001b[39m, props\u001b[38;5;241m=\u001b[39mparams)\n\u001b[1;32m--> 469\u001b[0m Xt \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_fit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrouted_params\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    470\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _print_elapsed_time(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPipeline\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_log_message(\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msteps) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m)):\n\u001b[0;32m    471\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_final_estimator \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpassthrough\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\pipeline.py:406\u001b[0m, in \u001b[0;36mPipeline._fit\u001b[1;34m(self, X, y, routed_params)\u001b[0m\n\u001b[0;32m    404\u001b[0m     cloned_transformer \u001b[38;5;241m=\u001b[39m clone(transformer)\n\u001b[0;32m    405\u001b[0m \u001b[38;5;66;03m# Fit or load from cache the current transformer\u001b[39;00m\n\u001b[1;32m--> 406\u001b[0m X, fitted_transformer \u001b[38;5;241m=\u001b[39m \u001b[43mfit_transform_one_cached\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    407\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcloned_transformer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    408\u001b[0m \u001b[43m    \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    409\u001b[0m \u001b[43m    \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    410\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m    411\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmessage_clsname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mPipeline\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    412\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmessage\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_log_message\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstep_idx\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    413\u001b[0m \u001b[43m    \u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrouted_params\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    414\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    415\u001b[0m \u001b[38;5;66;03m# Replace the transformer of the step with the fitted\u001b[39;00m\n\u001b[0;32m    416\u001b[0m \u001b[38;5;66;03m# transformer. This is necessary when loading the transformer\u001b[39;00m\n\u001b[0;32m    417\u001b[0m \u001b[38;5;66;03m# from the cache.\u001b[39;00m\n\u001b[0;32m    418\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msteps[step_idx] \u001b[38;5;241m=\u001b[39m (name, fitted_transformer)\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\joblib\\memory.py:312\u001b[0m, in \u001b[0;36mNotMemorizedFunc.__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m    311\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 312\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\pipeline.py:1310\u001b[0m, in \u001b[0;36m_fit_transform_one\u001b[1;34m(transformer, X, y, weight, message_clsname, message, params)\u001b[0m\n\u001b[0;32m   1308\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _print_elapsed_time(message_clsname, message):\n\u001b[0;32m   1309\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(transformer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfit_transform\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m-> 1310\u001b[0m         res \u001b[38;5;241m=\u001b[39m \u001b[43mtransformer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit_transform\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfit_transform\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1311\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m   1312\u001b[0m         res \u001b[38;5;241m=\u001b[39m transformer\u001b[38;5;241m.\u001b[39mfit(X, y, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfit\u001b[39m\u001b[38;5;124m\"\u001b[39m, {}))\u001b[38;5;241m.\u001b[39mtransform(\n\u001b[0;32m   1313\u001b[0m             X, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtransform\u001b[39m\u001b[38;5;124m\"\u001b[39m, {})\n\u001b[0;32m   1314\u001b[0m         )\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\base.py:1473\u001b[0m, in \u001b[0;36m_fit_context.<locals>.decorator.<locals>.wrapper\u001b[1;34m(estimator, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1466\u001b[0m     estimator\u001b[38;5;241m.\u001b[39m_validate_params()\n\u001b[0;32m   1468\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[0;32m   1469\u001b[0m     skip_parameter_validation\u001b[38;5;241m=\u001b[39m(\n\u001b[0;32m   1470\u001b[0m         prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[0;32m   1471\u001b[0m     )\n\u001b[0;32m   1472\u001b[0m ):\n\u001b[1;32m-> 1473\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfit_method\u001b[49m\u001b[43m(\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\pipeline.py:533\u001b[0m, in \u001b[0;36mPipeline.fit_transform\u001b[1;34m(self, X, y, **params)\u001b[0m\n\u001b[0;32m    490\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Fit the model and transform with the final estimator.\u001b[39;00m\n\u001b[0;32m    491\u001b[0m \n\u001b[0;32m    492\u001b[0m \u001b[38;5;124;03mFit all the transformers one after the other and sequentially transform\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    530\u001b[0m \u001b[38;5;124;03m    Transformed samples.\u001b[39;00m\n\u001b[0;32m    531\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m    532\u001b[0m routed_params \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_method_params(method\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfit_transform\u001b[39m\u001b[38;5;124m\"\u001b[39m, props\u001b[38;5;241m=\u001b[39mparams)\n\u001b[1;32m--> 533\u001b[0m Xt \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_fit\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrouted_params\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    535\u001b[0m last_step \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_final_estimator\n\u001b[0;32m    536\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _print_elapsed_time(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPipeline\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_log_message(\u001b[38;5;28mlen\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msteps) \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1\u001b[39m)):\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\pipeline.py:406\u001b[0m, in \u001b[0;36mPipeline._fit\u001b[1;34m(self, X, y, routed_params)\u001b[0m\n\u001b[0;32m    404\u001b[0m     cloned_transformer \u001b[38;5;241m=\u001b[39m clone(transformer)\n\u001b[0;32m    405\u001b[0m \u001b[38;5;66;03m# Fit or load from cache the current transformer\u001b[39;00m\n\u001b[1;32m--> 406\u001b[0m X, fitted_transformer \u001b[38;5;241m=\u001b[39m \u001b[43mfit_transform_one_cached\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    407\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcloned_transformer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    408\u001b[0m \u001b[43m    \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    409\u001b[0m \u001b[43m    \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    410\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[0;32m    411\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmessage_clsname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mPipeline\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m    412\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmessage\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_log_message\u001b[49m\u001b[43m(\u001b[49m\u001b[43mstep_idx\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    413\u001b[0m \u001b[43m    \u001b[49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrouted_params\u001b[49m\u001b[43m[\u001b[49m\u001b[43mname\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m    414\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    415\u001b[0m \u001b[38;5;66;03m# Replace the transformer of the step with the fitted\u001b[39;00m\n\u001b[0;32m    416\u001b[0m \u001b[38;5;66;03m# transformer. This is necessary when loading the transformer\u001b[39;00m\n\u001b[0;32m    417\u001b[0m \u001b[38;5;66;03m# from the cache.\u001b[39;00m\n\u001b[0;32m    418\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msteps[step_idx] \u001b[38;5;241m=\u001b[39m (name, fitted_transformer)\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\joblib\\memory.py:312\u001b[0m, in \u001b[0;36mNotMemorizedFunc.__call__\u001b[1;34m(self, *args, **kwargs)\u001b[0m\n\u001b[0;32m    311\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__call__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 312\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\pipeline.py:1310\u001b[0m, in \u001b[0;36m_fit_transform_one\u001b[1;34m(transformer, X, y, weight, message_clsname, message, params)\u001b[0m\n\u001b[0;32m   1308\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _print_elapsed_time(message_clsname, message):\n\u001b[0;32m   1309\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(transformer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfit_transform\u001b[39m\u001b[38;5;124m\"\u001b[39m):\n\u001b[1;32m-> 1310\u001b[0m         res \u001b[38;5;241m=\u001b[39m \u001b[43mtransformer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit_transform\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43my\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mparams\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfit_transform\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m   1311\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m   1312\u001b[0m         res \u001b[38;5;241m=\u001b[39m transformer\u001b[38;5;241m.\u001b[39mfit(X, y, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfit\u001b[39m\u001b[38;5;124m\"\u001b[39m, {}))\u001b[38;5;241m.\u001b[39mtransform(\n\u001b[0;32m   1313\u001b[0m             X, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtransform\u001b[39m\u001b[38;5;124m\"\u001b[39m, {})\n\u001b[0;32m   1314\u001b[0m         )\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\utils\\_set_output.py:316\u001b[0m, in \u001b[0;36m_wrap_method_output.<locals>.wrapped\u001b[1;34m(self, X, *args, **kwargs)\u001b[0m\n\u001b[0;32m    314\u001b[0m \u001b[38;5;129m@wraps\u001b[39m(f)\n\u001b[0;32m    315\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mwrapped\u001b[39m(\u001b[38;5;28mself\u001b[39m, X, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m--> 316\u001b[0m     data_to_wrap \u001b[38;5;241m=\u001b[39m \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    317\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data_to_wrap, \u001b[38;5;28mtuple\u001b[39m):\n\u001b[0;32m    318\u001b[0m         \u001b[38;5;66;03m# only wrap the first output for cross decomposition\u001b[39;00m\n\u001b[0;32m    319\u001b[0m         return_tuple \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m    320\u001b[0m             _wrap_data_with_container(method, data_to_wrap[\u001b[38;5;241m0\u001b[39m], X, \u001b[38;5;28mself\u001b[39m),\n\u001b[0;32m    321\u001b[0m             \u001b[38;5;241m*\u001b[39mdata_to_wrap[\u001b[38;5;241m1\u001b[39m:],\n\u001b[0;32m    322\u001b[0m         )\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\base.py:1473\u001b[0m, in \u001b[0;36m_fit_context.<locals>.decorator.<locals>.wrapper\u001b[1;34m(estimator, *args, **kwargs)\u001b[0m\n\u001b[0;32m   1466\u001b[0m     estimator\u001b[38;5;241m.\u001b[39m_validate_params()\n\u001b[0;32m   1468\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m config_context(\n\u001b[0;32m   1469\u001b[0m     skip_parameter_validation\u001b[38;5;241m=\u001b[39m(\n\u001b[0;32m   1470\u001b[0m         prefer_skip_nested_validation \u001b[38;5;129;01mor\u001b[39;00m global_skip_validation\n\u001b[0;32m   1471\u001b[0m     )\n\u001b[0;32m   1472\u001b[0m ):\n\u001b[1;32m-> 1473\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfit_method\u001b[49m\u001b[43m(\u001b[49m\u001b[43mestimator\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\compose\\_column_transformer.py:968\u001b[0m, in \u001b[0;36mColumnTransformer.fit_transform\u001b[1;34m(self, X, y, **params)\u001b[0m\n\u001b[0;32m    965\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_transformers()\n\u001b[0;32m    966\u001b[0m n_samples \u001b[38;5;241m=\u001b[39m _num_samples(X)\n\u001b[1;32m--> 968\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_validate_column_callables\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    969\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_remainder(X)\n\u001b[0;32m    971\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m _routing_enabled():\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\compose\\_column_transformer.py:536\u001b[0m, in \u001b[0;36mColumnTransformer._validate_column_callables\u001b[1;34m(self, X)\u001b[0m\n\u001b[0;32m    534\u001b[0m         columns \u001b[38;5;241m=\u001b[39m columns(X)\n\u001b[0;32m    535\u001b[0m     all_columns\u001b[38;5;241m.\u001b[39mappend(columns)\n\u001b[1;32m--> 536\u001b[0m     transformer_to_input_indices[name] \u001b[38;5;241m=\u001b[39m \u001b[43m_get_column_indices\u001b[49m\u001b[43m(\u001b[49m\u001b[43mX\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    538\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_columns \u001b[38;5;241m=\u001b[39m all_columns\n\u001b[0;32m    539\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transformer_to_input_indices \u001b[38;5;241m=\u001b[39m transformer_to_input_indices\n",
+      "File \u001b[1;32md:\\Study\\3 курс 5 семестр\\AIM\\AIM-PIbd-31-Yakovlev-M-G\\kernel\\Lib\\site-packages\\sklearn\\utils\\_indexing.py:340\u001b[0m, in \u001b[0;36m_get_column_indices\u001b[1;34m(X, key)\u001b[0m\n\u001b[0;32m    338\u001b[0m     all_columns \u001b[38;5;241m=\u001b[39m X\u001b[38;5;241m.\u001b[39mcolumns\n\u001b[0;32m    339\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mAttributeError\u001b[39;00m:\n\u001b[1;32m--> 340\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[0;32m    341\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSpecifying the columns using strings is only supported for dataframes.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    342\u001b[0m     )\n\u001b[0;32m    343\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(key, \u001b[38;5;28mstr\u001b[39m):\n\u001b[0;32m    344\u001b[0m     columns \u001b[38;5;241m=\u001b[39m [key]\n",
+      "\u001b[1;31mValueError\u001b[0m: Specifying the columns using strings is only supported for dataframes."
+     ]
+    }
+   ],
+   "source": [
+    "import numpy as np\n",
+    "from sklearn import metrics\n",
+    "\n",
+    "for model_name in class_models.keys():\n",
+    "    print(f\"Model: {model_name}\")\n",
+    "    model = class_models[model_name][\"model\"]\n",
+    "\n",
+    "    model_pipeline = Pipeline([(\"pipeline\", pipeline_end), (\"model\", model)])\n",
+    "    model_pipeline = model_pipeline.fit(X_train, y_train.values.ravel())\n",
+    "\n",
+    "    y_train_predict = model_pipeline.predict(X_train)\n",
+    "    y_test_probs = model_pipeline.predict_proba(X_test)[:, 1]\n",
+    "    y_test_predict = np.where(y_test_probs > 0.5, 1, 0)\n",
+    "\n",
+    "    class_models[model_name][\"pipeline\"] = model_pipeline\n",
+    "    class_models[model_name][\"probs\"] = y_test_probs\n",
+    "    class_models[model_name][\"preds\"] = y_test_predict\n",
+    "\n",
+    "    class_models[model_name][\"Precision_train\"] = metrics.precision_score(\n",
+    "        y_train, y_train_predict\n",
+    "    )\n",
+    "    class_models[model_name][\"Precision_test\"] = metrics.precision_score(\n",
+    "        y_test, y_test_predict\n",
+    "    )\n",
+    "    class_models[model_name][\"Recall_train\"] = metrics.recall_score(\n",
+    "        y_train, y_train_predict\n",
+    "    )\n",
+    "    class_models[model_name][\"Recall_test\"] = metrics.recall_score(\n",
+    "        y_test, y_test_predict\n",
+    "    )\n",
+    "    class_models[model_name][\"Accuracy_train\"] = metrics.accuracy_score(\n",
+    "        y_train, y_train_predict\n",
+    "    )\n",
+    "    class_models[model_name][\"Accuracy_test\"] = metrics.accuracy_score(\n",
+    "        y_test, y_test_predict\n",
+    "    )\n",
+    "    class_models[model_name][\"ROC_AUC_test\"] = metrics.roc_auc_score(\n",
+    "        y_test, y_test_probs\n",
+    "    )\n",
+    "    class_models[model_name][\"F1_train\"] = metrics.f1_score(y_train, y_train_predict)\n",
+    "    class_models[model_name][\"F1_test\"] = metrics.f1_score(y_test, y_test_predict)\n",
+    "    class_models[model_name][\"MCC_test\"] = metrics.matthews_corrcoef(\n",
+    "        y_test, y_test_predict\n",
+    "    )\n",
+    "    class_models[model_name][\"Cohen_kappa_test\"] = metrics.cohen_kappa_score(\n",
+    "        y_test, y_test_predict\n",
+    "    )\n",
+    "    class_models[model_name][\"Confusion_matrix\"] = metrics.confusion_matrix(\n",
+    "        y_test, y_test_predict\n",
+    "    )"
    ]
   }
  ],