From 271ccaf83567806b464e4feb8fb537ae5abd5a08 Mon Sep 17 00:00:00 2001
From: "a.puchkina" <anna.puchkina.04>
Date: Sat, 8 Feb 2025 13:36:03 +0400
Subject: [PATCH] =?UTF-8?q?=D0=9B=D0=90=D0=91=D0=90=207?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 lab_7/lab7.ipynb | 2357 +++++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 2355 insertions(+), 2 deletions(-)

diff --git a/lab_7/lab7.ipynb b/lab_7/lab7.ipynb
index 2b2a962..2658522 100644
--- a/lab_7/lab7.ipynb
+++ b/lab_7/lab7.ipynb
@@ -7,15 +7,2368 @@
     "# Начало лабораторной работы №7 #"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['Unnamed: 0', 'Name', 'Brand', 'Model', 'Battery capacity (mAh)',\n",
+      "       'Screen size (inches)', 'Touchscreen', 'Resolution x', 'Resolution y',\n",
+      "       'Processor', 'RAM (MB)', 'Internal storage (GB)', 'Rear camera',\n",
+      "       'Front camera', 'Operating system', 'Wi-Fi', 'Bluetooth', 'GPS',\n",
+      "       'Number of SIMs', '3G', '4G/ LTE', 'Price'],\n",
+      "      dtype='object')\n"
+     ]
+    },
+    {
+     "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>Unnamed: 0</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Brand</th>\n",
+       "      <th>Model</th>\n",
+       "      <th>Battery capacity (mAh)</th>\n",
+       "      <th>Screen size (inches)</th>\n",
+       "      <th>Touchscreen</th>\n",
+       "      <th>Resolution x</th>\n",
+       "      <th>Resolution y</th>\n",
+       "      <th>Processor</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Rear camera</th>\n",
+       "      <th>Front camera</th>\n",
+       "      <th>Operating system</th>\n",
+       "      <th>Wi-Fi</th>\n",
+       "      <th>Bluetooth</th>\n",
+       "      <th>GPS</th>\n",
+       "      <th>Number of SIMs</th>\n",
+       "      <th>3G</th>\n",
+       "      <th>4G/ LTE</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>OnePlus 7T Pro McLaren Edition</td>\n",
+       "      <td>OnePlus</td>\n",
+       "      <td>7T Pro McLaren Edition</td>\n",
+       "      <td>4085</td>\n",
+       "      <td>6.67</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1440</td>\n",
+       "      <td>3120</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>58998</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Realme X2 Pro</td>\n",
+       "      <td>Realme</td>\n",
+       "      <td>X2 Pro</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>27999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>Apple</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>3969</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1242</td>\n",
+       "      <td>2688</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>iOS</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>106900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>iPhone 11</td>\n",
+       "      <td>Apple</td>\n",
+       "      <td>iPhone 11</td>\n",
+       "      <td>3110</td>\n",
+       "      <td>6.10</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>828</td>\n",
+       "      <td>1792</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>iOS</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>62900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>LG G8X ThinQ</td>\n",
+       "      <td>LG</td>\n",
+       "      <td>G8X ThinQ</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.40</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1</td>\n",
+       "      <td>No</td>\n",
+       "      <td>No</td>\n",
+       "      <td>49990</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 22 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unnamed: 0                            Name    Brand  \\\n",
+       "0           0  OnePlus 7T Pro McLaren Edition  OnePlus   \n",
+       "1           1                   Realme X2 Pro   Realme   \n",
+       "2           2               iPhone 11 Pro Max    Apple   \n",
+       "3           3                       iPhone 11    Apple   \n",
+       "4           4                    LG G8X ThinQ       LG   \n",
+       "\n",
+       "                    Model  Battery capacity (mAh)  Screen size (inches)  \\\n",
+       "0  7T Pro McLaren Edition                    4085                  6.67   \n",
+       "1                  X2 Pro                    4000                  6.50   \n",
+       "2       iPhone 11 Pro Max                    3969                  6.50   \n",
+       "3               iPhone 11                    3110                  6.10   \n",
+       "4               G8X ThinQ                    4000                  6.40   \n",
+       "\n",
+       "  Touchscreen  Resolution x  Resolution y  Processor  ...  Rear camera  \\\n",
+       "0         Yes          1440          3120          8  ...         48.0   \n",
+       "1         Yes          1080          2400          8  ...         64.0   \n",
+       "2         Yes          1242          2688          6  ...         12.0   \n",
+       "3         Yes           828          1792          6  ...         12.0   \n",
+       "4         Yes          1080          2340          8  ...         12.0   \n",
+       "\n",
+       "   Front camera  Operating system  Wi-Fi Bluetooth  GPS Number of SIMs   3G  \\\n",
+       "0          16.0           Android    Yes       Yes  Yes              2  Yes   \n",
+       "1          16.0           Android    Yes       Yes  Yes              2  Yes   \n",
+       "2          12.0               iOS    Yes       Yes  Yes              2  Yes   \n",
+       "3          12.0               iOS    Yes       Yes  Yes              2  Yes   \n",
+       "4          32.0           Android    Yes       Yes  Yes              1   No   \n",
+       "\n",
+       "   4G/ LTE   Price  \n",
+       "0      Yes   58998  \n",
+       "1      Yes   27999  \n",
+       "2      Yes  106900  \n",
+       "3      Yes   62900  \n",
+       "4       No   49990  \n",
+       "\n",
+       "[5 rows x 22 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "df = pd.read_csv(\"..//static//csv//ndtv_data_final.csv\")\n",
+    "print(df.columns)\n",
+    "display(df.head())"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
-   "source": []
+   "source": [
+    "\n",
+    "**Создание лингвистических переменных**\n",
+    "\n",
+    "Входные переменные: Battery capacity (mAh) (емкость батареи) и RAM (MB) (объем оперативной памяти). \\\n",
+    "Выходная переменная: Price (цена)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 120,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "from skfuzzy import control as ctrl\n",
+    "\n",
+    "data = pd.read_csv(\"..//static//csv//ndtv_data_final.csv\")\n",
+    "\n",
+    "# Инициализация лингвистических переменных\n",
+    "battery_capacity = ctrl.Antecedent(np.arange(data['Battery capacity (mAh)'].min(), data['Battery capacity (mAh)'].max(), 100), \"battery_capacity\")\n",
+    "ram = ctrl.Antecedent(np.arange(data['RAM (MB)'].min(), data['RAM (MB)'].max(), 100), \"ram\")\n",
+    "price = ctrl.Consequent(np.arange(data['Price'].min(), data['Price'].max(), 10), \"price\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Формирование нечетких переменных для лингвистических переменных и их визуализация**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 121,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\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": [
+    "import skfuzzy as fuzz\n",
+    "\n",
+    "battery_capacity['low'] = fuzz.zmf(battery_capacity.universe, 2000, 3000)\n",
+    "battery_capacity['average'] = fuzz.trapmf(battery_capacity.universe, [2000, 3000, 4000, 5000])\n",
+    "battery_capacity['high'] = fuzz.smf(battery_capacity.universe, 4000, 5000)\n",
+    "\n",
+    "ram['low'] = fuzz.zmf(ram.universe, 1000, 2000)\n",
+    "ram['average'] = fuzz.trapmf(ram.universe, [1000, 2000, 4000, 6000])\n",
+    "ram['high'] = fuzz.smf(ram.universe, 4000, 6000)\n",
+    "\n",
+    "price['low'] = fuzz.zmf(price.universe, 10000, 20000)\n",
+    "price['average'] = fuzz.trapmf(price.universe, [10000, 20000, 40000, 60000])\n",
+    "price['high'] = fuzz.smf(price.universe, 40000, 60000)\n",
+    "\n",
+    "battery_capacity.view()\n",
+    "ram.view()\n",
+    "price.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Формирование и визуализация базы нечетких правил**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 122,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(<Figure size 640x480 with 1 Axes>, <Axes: >)"
+      ]
+     },
+     "execution_count": 122,
+     "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": [
+    "# Нечеткие правила\n",
+    "rule1 = ctrl.Rule(battery_capacity[\"low\"] & ram[\"low\"], price[\"low\"])\n",
+    "rule2 = ctrl.Rule(battery_capacity[\"low\"] & ram[\"average\"], price[\"low\"])\n",
+    "rule3 = ctrl.Rule(battery_capacity[\"low\"] & ram[\"high\"], price[\"average\"])\n",
+    "rule4 = ctrl.Rule(battery_capacity[\"average\"] & ram[\"low\"], price[\"low\"])\n",
+    "rule5 = ctrl.Rule(battery_capacity[\"average\"] & ram[\"average\"], price[\"average\"])\n",
+    "rule6 = ctrl.Rule(battery_capacity[\"average\"] & ram[\"high\"], price[\"high\"])\n",
+    "rule7 = ctrl.Rule(battery_capacity[\"high\"] & ram[\"low\"], price[\"average\"])\n",
+    "rule8 = ctrl.Rule(battery_capacity[\"high\"] & ram[\"average\"], price[\"high\"])\n",
+    "rule9 = ctrl.Rule(battery_capacity[\"high\"] & ram[\"high\"], price[\"high\"])\n",
+    "rule1.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Создание нечеткой системы и добавление нечетких правил в базу знаний нечеткой системы**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 123,
+   "metadata": {},
+   "outputs": [],
+   "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",
+    "# Создание симулятора нечеткой системы\n",
+    "price_sim = ctrl.ControlSystemSimulation(price_ctrl)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Пример расчета выходной переменной influx на основе входных переменных level и flow** \\\n",
+    "Система также формирует подробный журнал выполнения процесса нечеткого логического вывода"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 124,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: battery_capacity        = 4000\n",
+      "  - low                             : 0.0\n",
+      "  - average                         : 0.991\n",
+      "  - high                            : 0.00017999999999999998\n",
+      "Antecedent: ram                     = 2000\n",
+      "  - low                             : 0.0016588799999999997\n",
+      "  - average                         : 0.9769599999999999\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF battery_capacity[low] AND ram[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[low]                                  : 0.0\n",
+      "  - ram[low]                                               : 0.0016588799999999997\n",
+      "                        battery_capacity[low] AND ram[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF battery_capacity[low] AND ram[average] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[low]                                  : 0.0\n",
+      "  - ram[average]                                           : 0.9769599999999999\n",
+      "                    battery_capacity[low] AND ram[average] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF battery_capacity[low] AND ram[high] THEN price[average]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[low]                                  : 0.0\n",
+      "  - ram[high]                                              : 0.0\n",
+      "                       battery_capacity[low] AND ram[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                            price[average] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF battery_capacity[average] AND ram[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[average]                              : 0.991\n",
+      "  - ram[low]                                               : 0.0016588799999999997\n",
+      "                    battery_capacity[average] AND ram[low] = 0.0016588799999999997\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.0016588799999999997\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF battery_capacity[average] AND ram[average] THEN price[average]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[average]                              : 0.991\n",
+      "  - ram[average]                                           : 0.9769599999999999\n",
+      "                battery_capacity[average] AND ram[average] = 0.9769599999999999\n",
+      "  Activation (THEN-clause):\n",
+      "                                            price[average] : 0.9769599999999999\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF battery_capacity[average] AND ram[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[average]                              : 0.991\n",
+      "  - ram[high]                                              : 0.0\n",
+      "                   battery_capacity[average] AND ram[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF battery_capacity[high] AND ram[low] THEN price[average]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[high]                                 : 0.00017999999999999998\n",
+      "  - ram[low]                                               : 0.0016588799999999997\n",
+      "                       battery_capacity[high] AND ram[low] = 0.00017999999999999998\n",
+      "  Activation (THEN-clause):\n",
+      "                                            price[average] : 0.00017999999999999998\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF battery_capacity[high] AND ram[average] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[high]                                 : 0.00017999999999999998\n",
+      "  - ram[average]                                           : 0.9769599999999999\n",
+      "                   battery_capacity[high] AND ram[average] = 0.00017999999999999998\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.00017999999999999998\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF battery_capacity[high] AND ram[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[high]                                 : 0.00017999999999999998\n",
+      "  - ram[high]                                              : 0.0\n",
+      "                      battery_capacity[high] AND ram[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 32933.17210826396\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.0016588799999999997\n",
+      "  average:\n",
+      "    Accumulate using accumulation_max : 0.9769599999999999\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.00017999999999999998\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(32933.17210826396)"
+      ]
+     },
+     "execution_count": 124,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "price_sim.input['battery_capacity'] = 4000\n",
+    "price_sim.input['ram'] = 2000\n",
+    "price_sim.compute()\n",
+    "\n",
+    "price_sim.print_state()\n",
+    "\n",
+    "price_sim.output[\"price\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Визуализация функции принадлежности для выходной переменной influx** /\n",
+    "Функция получена в процессе аккумуляции и используется для дефаззификации значения выходной переменной influx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 125,
+   "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=price_sim)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "### Пример решения задачи регрессии на основе нечеткого логического вывода ###\n",
+    "\n",
+    "**Загрузка данных**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 126,
+   "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>Unnamed: 0</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Brand</th>\n",
+       "      <th>Model</th>\n",
+       "      <th>Battery capacity (mAh)</th>\n",
+       "      <th>Screen size (inches)</th>\n",
+       "      <th>Touchscreen</th>\n",
+       "      <th>Resolution x</th>\n",
+       "      <th>Resolution y</th>\n",
+       "      <th>Processor</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Rear camera</th>\n",
+       "      <th>Front camera</th>\n",
+       "      <th>Operating system</th>\n",
+       "      <th>Wi-Fi</th>\n",
+       "      <th>Bluetooth</th>\n",
+       "      <th>GPS</th>\n",
+       "      <th>Number of SIMs</th>\n",
+       "      <th>3G</th>\n",
+       "      <th>4G/ LTE</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>OnePlus 7T Pro McLaren Edition</td>\n",
+       "      <td>OnePlus</td>\n",
+       "      <td>7T Pro McLaren Edition</td>\n",
+       "      <td>4085</td>\n",
+       "      <td>6.67</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1440</td>\n",
+       "      <td>3120</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>58998</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Realme X2 Pro</td>\n",
+       "      <td>Realme</td>\n",
+       "      <td>X2 Pro</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>27999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>Apple</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>3969</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1242</td>\n",
+       "      <td>2688</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>iOS</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>106900</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3 rows × 22 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unnamed: 0                            Name    Brand  \\\n",
+       "0           0  OnePlus 7T Pro McLaren Edition  OnePlus   \n",
+       "1           1                   Realme X2 Pro   Realme   \n",
+       "2           2               iPhone 11 Pro Max    Apple   \n",
+       "\n",
+       "                    Model  Battery capacity (mAh)  Screen size (inches)  \\\n",
+       "0  7T Pro McLaren Edition                    4085                  6.67   \n",
+       "1                  X2 Pro                    4000                  6.50   \n",
+       "2       iPhone 11 Pro Max                    3969                  6.50   \n",
+       "\n",
+       "  Touchscreen  Resolution x  Resolution y  Processor  ...  Rear camera  \\\n",
+       "0         Yes          1440          3120          8  ...         48.0   \n",
+       "1         Yes          1080          2400          8  ...         64.0   \n",
+       "2         Yes          1242          2688          6  ...         12.0   \n",
+       "\n",
+       "   Front camera  Operating system  Wi-Fi Bluetooth  GPS Number of SIMs   3G  \\\n",
+       "0          16.0           Android    Yes       Yes  Yes              2  Yes   \n",
+       "1          16.0           Android    Yes       Yes  Yes              2  Yes   \n",
+       "2          12.0               iOS    Yes       Yes  Yes              2  Yes   \n",
+       "\n",
+       "   4G/ LTE   Price  \n",
+       "0      Yes   58998  \n",
+       "1      Yes   27999  \n",
+       "2      Yes  106900  \n",
+       "\n",
+       "[3 rows x 22 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "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>Unnamed: 0</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Brand</th>\n",
+       "      <th>Model</th>\n",
+       "      <th>Battery capacity (mAh)</th>\n",
+       "      <th>Screen size (inches)</th>\n",
+       "      <th>Touchscreen</th>\n",
+       "      <th>Resolution x</th>\n",
+       "      <th>Resolution y</th>\n",
+       "      <th>Processor</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Rear camera</th>\n",
+       "      <th>Front camera</th>\n",
+       "      <th>Operating system</th>\n",
+       "      <th>Wi-Fi</th>\n",
+       "      <th>Bluetooth</th>\n",
+       "      <th>GPS</th>\n",
+       "      <th>Number of SIMs</th>\n",
+       "      <th>3G</th>\n",
+       "      <th>4G/ LTE</th>\n",
+       "      <th>Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>OnePlus 7T Pro McLaren Edition</td>\n",
+       "      <td>OnePlus</td>\n",
+       "      <td>7T Pro McLaren Edition</td>\n",
+       "      <td>4085</td>\n",
+       "      <td>6.67</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1440</td>\n",
+       "      <td>3120</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>48.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>58998</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Realme X2 Pro</td>\n",
+       "      <td>Realme</td>\n",
+       "      <td>X2 Pro</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>64.0</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>27999</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>Apple</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>3969</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1242</td>\n",
+       "      <td>2688</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>iOS</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>106900</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3 rows × 22 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Unnamed: 0                            Name    Brand  \\\n",
+       "0           0  OnePlus 7T Pro McLaren Edition  OnePlus   \n",
+       "1           1                   Realme X2 Pro   Realme   \n",
+       "2           2               iPhone 11 Pro Max    Apple   \n",
+       "\n",
+       "                    Model  Battery capacity (mAh)  Screen size (inches)  \\\n",
+       "0  7T Pro McLaren Edition                    4085                  6.67   \n",
+       "1                  X2 Pro                    4000                  6.50   \n",
+       "2       iPhone 11 Pro Max                    3969                  6.50   \n",
+       "\n",
+       "  Touchscreen  Resolution x  Resolution y  Processor  ...  Rear camera  \\\n",
+       "0         Yes          1440          3120          8  ...         48.0   \n",
+       "1         Yes          1080          2400          8  ...         64.0   \n",
+       "2         Yes          1242          2688          6  ...         12.0   \n",
+       "\n",
+       "   Front camera  Operating system  Wi-Fi Bluetooth  GPS Number of SIMs   3G  \\\n",
+       "0          16.0           Android    Yes       Yes  Yes              2  Yes   \n",
+       "1          16.0           Android    Yes       Yes  Yes              2  Yes   \n",
+       "2          12.0               iOS    Yes       Yes  Yes              2  Yes   \n",
+       "\n",
+       "   4G/ LTE   Price  \n",
+       "0      Yes   58998  \n",
+       "1      Yes   27999  \n",
+       "2      Yes  106900  \n",
+       "\n",
+       "[3 rows x 22 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "data_train = pd.read_csv(\"..//static//csv//ndtv_data_final.csv\", sep=\",\")\n",
+    "data_test = pd.read_csv(\"..//static//csv//ndtv_data_final.csv\", sep=\",\")\n",
+    "\n",
+    "display(data_train.head(3))\n",
+    "display(data_test.head(3))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Инициализация лингвистических переменных и автоматическое формирование нечетких переменных**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 127,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "d:\\ULSTU\\AIM2\\AIM-PIbd-32-Puchkina-A-A\\aimenv\\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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nbcXcN3y5cCee+dvOq44jRM5KuA9rB0LZllDTsma1PJO1neEG9OgzsHOm6jRC5KjYpFgm7puIf1F/Xiv3muo4OUoKpFxSpYgLg5uXY/GOixyLfKA6jhA5Z9MoSH0MneaDRqM6Te4o7ANNRhvuRbp+WHUaIXLMtAPTSExLZFKDSWgs/PyWAikX9WtahqpFXRi+KpzEFBlqExbo9Fo4sRLazgbnIqrT5K6GQw395Vb3hZTHqtMIYXRbrm5h4+WNjKk7Bs98nqrj5DgpkHKRtZWWud18uf7gMXM2n1UdRwjjio+G9UOhYgfweUN1mtxnZW2Y1RYTaVgfSQgLcu/xPaaETuEV71foULqD6ji5QgqkXFbO04kRrcrzzd7LHLx8X3UcIYxDr4cNQwE9dJiXd4bW/qtQRcP6SKEL4eo+1WmEMAq9Xs/U/Yaif3yD8RY/tPY/UiAp8H7D0tQq7saIVeE8SpIF5oQFOPE7RKyD9p9B/oKq06jVoD941zPMakuKV51GiGzbcHkDWyO3ElA/AA8HD9Vxco0USApYaTXM6eZL9MMkpm+KUB1HiOyJuwUbh0PV16FKF9Vp1NNaQZdFEH8HtgSqTiNEttxJuMO0A9NoW6otrUq2Uh0nV0mBpEhJj3yMaVeRn/ZHsvt8tOo4QmSNXg/rBoG1PbSbrTqN6ShQBlpMgsPfwMW/VacRIkv0ej0T9k3AzsqOcfXGqY6T66RAUqhXvRL4lSnAyN+PE5eYojqOEJl37Ec4/xd0nA+O7qrTmJY6H0CpxoZ2K4myir4wP6svrGbPjT1MbDARFzsX1XFynRRICmm1Gma97sPDxFSmrDutOo4QmRMTCSFjoXovqNBGdRrTo9Ua2qwkxhl+TkKYkZvxN5l1aBZdynahiXcT1XGUkAJJsWJujozvUIlVR66zLeK26jhCZIxOB2v6g70LtJmmOo3pci1u+PmE/QRnQ1SnESJDdHodgXsDcbJ1YmSdkarjKCMFkgl4o7Y3zSoUZPSfJ3jwKFl1HCFe7vA3cHkXdF5gKJLE89V4G8q1MtyrlSBLewjT99uZ3zgQdYDJfpNxsnVSHUcZKZBMgEajYcZrPiSn6ghce0p1HCFe7N5Fw+ysOh9AmWaq05g+jcZwj1ZqEmwcoTqNEC90Ne4q847Oo3uF7jQo0kB1HKWkQDIRns72TO5chXXhN9lw/JbqOEI8my4Ngj+B/IUMs7RExjgXNszyO/kHnFqtOo0Qz5SmSyNgTwAF7AswrNYw1XGUkwLJhHTyLUKbKl4EBJ8g+mGS6jhCPC10IVw7YOheb5dfdRrzUq0bVOoI64cZ1kgSwsT8ePpHwqPDmdpwKo42jqrjKCcFkgnRaDRM7VoVrUbDuNUn0Ov1qiMJ8Y87Zww9xhr0hxJ+qtOYH40G2n9u+N/1Qw1rSAlhIi7GXOTLY1/yduW3qeVZS3UckyAFkonxyG9HUNeq/HX6NquP3VAdRwiDtFQI7gtuJQy9xkTW5C9o6FV3Zj0cX6E6jRAApOhSGLdnHEWdijKwxkDVcUyGFEgmqE3VwnSpXoQJa09xK/ax6jhCwJ7P4Va4oVu9jYPqNOatcifDcNvGkRArH4KEet+c+IaI+xEE+Qdhb22vOo7JkALJRE3qVBUHGytG/SFDbUKxW8dh5wxoOAyKyaV3o2g7y1Borh0oQ21CqTP3z7A0fCnvV32fagWrqY5jUqRAMlEujjbMfM2HXeei+e3QNdVxRF6VmmToSl+wIjQZpTqN5XB0h05fwsVtcPR71WlEHpWclszYPWMp7Vqafr79VMcxOVIgmbBmFQvRvbY3U9ef5tr9BNVxRF60cyZEn4WuS8DaVnUay1K+lWERyc3j4MFV1WlEHrQkfAmXYy8zreE0bKxsVMcxOVIgmbiADpVwdbTl09/D0enkUrzIRdcPG+49ajIKvOTSe45oPQ0c3AxtW3Q61WlEHnI8+jjfnPyGvj59qeBeQXUckyQFkolzsrdh9us+7L90n+9Dr6iOI/KKlMewui8Urg4Nh6pOY7nsnQ3tWq7shoNfqU4j8ojE1ETG7RlHZffKvF/tfdVxTJYUSGbAr6wHfRqUYGbIGS5Fx6uOI/KCv6dCTKRhaM3KWnUay1a6KdT5ELZOhLsXVKcRecD8Y/O5GX+ToIZBWGvl/H4eKZDMxKi2FfFytmfEqnDSZKhN5KSr+wwrZjcfDwXl0nuuaDkJnLwMN8Tr0lSnERbscNRhfjr9E4NqDqK0a2nVcUya8gJp4cKFlCxZEnt7e+rVq8fBgwdfuP28efOoUKECDg4OeHt7M3ToUBITE3MprTqOttbM6ebLsWsxLNt9SXUcYamS4g1/pL3rQf1PVKfJO2zzGa7WXT8E+75UnUZYqISUBAL2BlC9UHV6VeqlOo7JU1ogrVixgmHDhjFhwgSOHj2Kr68vrVu35s6dZ/cp+uWXXxg9ejQTJkwgIiKCb775hhUrVjB27NhcTq5G7ZLufNioNJ/9dY6zUQ9VxxGWaEugoU9Yl0WgtVKdJm8pXh/8BsD2ILh9WnUaYYE+O/IZ9xPvM9V/KlZyfr+U0gLps88+48MPP+Tdd9+lcuXKLFmyBEdHR7799ttnbr9v3z78/f156623KFmyJK1ataJHjx4vvepkSYa1LE/xAo4MXxVGSprMehFGdPFvOPwNtJwMBcqoTpM3NQsAt1KGti5pKarTCAuy7+Y+VpxdwdBaQynuXFx1HLOgrEBKTk7myJEjtGjR4p8wWi0tWrQgNDT0ma/x8/PjyJEj6QXRpUuX2LhxI+3atXvucZKSkoiLi3viy5zZ21jx2Ru+RNx6yMLtckOnMJLEWFgzAEo1gdoyq0UZG3vouhiiTsLuuarTCAvxMPkhgXsDqVe4Ht0rdFcdx2woK5Du3r1LWloanp6eTzzu6elJVFTUM1/z1ltvMXnyZBo2bIiNjQ1lypShadOmLxximz59Oi4uLulf3t7eRv0+VPAp5kr/pmVY8PcFTt6IVR1HWIKQsZAYB50Xglb5rYl5W9Fa0GgY7JoNN8NUpxEWYObBmcSnxDPFbwpajZzfGWVWP6kdO3Ywbdo0Fi1axNGjR/nzzz/ZsGEDU6ZMee5rxowZQ2xsbPrXtWuW0bZjwCvlKO/pxLCVYSSlyqwXkQ1nQyDsJ2gzHVzN/wOERWg8EgpWMqxFlZqkOo0wYzuu7WDNxTWMqjOKwvkLq45jVpQVSB4eHlhZWXH79u0nHr99+zZeXl7PfM348eN5++23+eCDD6hWrRpdu3Zl2rRpTJ8+Hd1zVqG1s7PD2dn5iS9LYGutZe4bvly++4h5W8+rjiPMVcJ9WDcIyrWCGjKrxWRY2xpmtd27ADumq04jzFRMYgwT902kUdFGdCnbRXUcs6OsQLK1taVWrVps27Yt/TGdTse2bdto0KDBM1+TkJCA9j+X/62sDHfi58WO95UKOzOkRXmW7rzI0cgHquMIc7RxhOEKRcf5oNGoTiP+zasqNB0Ne7+Aa4dUpxFmaNqBaaToUpjoNxGNnN+ZpnSIbdiwYSxbtozvv/+eiIgI+vXrx6NHj3j33XcB6N27N2PGjEnfvmPHjixevJjffvuNy5cvs2XLFsaPH0/Hjh3TC6W85uPGpalWzJURK8N5nCxDbSITTq2Gk39AuzngLJfeTZL/EChSwzCrLVkaVouM23xlM5uubGJsvbEUciykOo5ZUrrGePfu3YmOjiYwMJCoqCiqV69OSEhI+o3bkZGRT1wxCggIQKPREBAQwI0bNyhYsCAdO3YkKChI1begnLWVlrndfGk/fzezNp9hQscqqiMJcxB/B9YPg0qdoNrrqtOI57Gyhi5LYGkj2DYZ2s5QnUiYgbuP7zJ1/1RalmhJu1LPn+UtXkyjz2NjU3Fxcbi4uBAbG2sx9yMBfL37ElM3RPDrh/VpUKaA6jjClOn1sKIXRO6H/gcgn4fqROJl9i2Av8ZBn/VQqpHqNMKE6fV6Bm8fTHh0OKs7r8bd3l11JLNlVrPYxPO951+KuiXd+fT3cOKTUlXHEabs+Ao4sx46fC7Fkbmo3w+K+8GaTyBJVtEXz7f+0nq2X9vO+PrjpTjKJimQLIRWq2F2Nx/uP0pm2sYI1XGEqYq9ARtHQrU3oHIn1WlERmmtoMtCeHQX/hqvOo0wUVGPoph+YDrtS7enRYkWL3+BeCEpkCxIiQL5GNOuEr8ciGTnuWjVcYSp0eth7UCwdYR2s1SnEZnlXhpaTYEj38GFrarTCBOj1+uZuG8iDtYOjKk75uUvEC8lBZKF6VWvOI3KeTDq9+PEPpZeTuJfjn4PF7dBpy/BwU11GpEVtd+H0k1hzUB4HKM6jTAhf5z/g7039zLRbyIudi6q41gEKZAsjEajYeZrPjxKSmXSulOq4whT8eAqbB4HNXtDuZaq04is0mig0wJIjocQuUogDG7E32D2odm8Vu41GhWTm/iNRQokC1TE1YHAjpX58+gN/jr17L52Ig/R6WBNf8NVo1Z5d0kMi+HqbWgLE/4LnNmoOo1QTKfXMX7veFzsXBhRe4TqOBZFCiQL9XqtYjSvWIixq09w/1Gy6jhCpYNfwZXdhka09paztEWeVr0nlG8D6wbDo3uq0wiFfj3zK4eiDjHFfwr5bfOrjmNRpECyUBqNhumvViNVp2f8mpOq4whV7l6ArROh7kdQuonqNMJYNBro+AWkJcPG4arTCEWuxF5h3pF59KjYg3qF66mOY3GkQLJghZztmdy5KhuO32Jd+E3VcURu06VBcD9DG5EWE1WnEcbm5AXt5/7TMkbkKWm6NAL2BlDIsRBDag5RHcciSYFk4Tr6FKZ9tcKMX3OSOw8TVccRuWnfl3D9EHRZDLb5VKcROaHqa1C5M2wYDg9vq04jctH3p7/nePRxpjaciqONo+o4FkkKJAun0WiY0qUq1loNY/88SR7rLJN33T4N24PAbyAUr686jcgpGg20/wy01rB+iGGtK2Hxzj84z4JjC3inyjvUKFRDdRyLJQVSHuCez5agrtXYGnGbP47eUB1H5LS0FEP3d/fS0Gyc6jQip+XzgA7z4OxGCP9VdRqRw1J0KYzbM47iTsXpX6O/6jgWTQqkPKJ1FS9erVGUSetOcTPmseo4IiftngtRJw1Dazb2qtOI3FCpA/i8CZtGQ+x11WlEDvr6+Nece3COoIZB2FnZqY5j0aRAykMmdKxCPltrRv1xXIbaLNXNMNg1GxoNh6I1VacRuantDEMbmbUDZajNQp2+d5qvjn/FB9U+oIpHFdVxLJ4USHmIi6MNM16rxu7zd/nlYKTqOMLYUpNgdV8oVAkaf6o6jchtDm6GVbYv/m3o1yYsSnJaMuP2jKOsW1k+9vlYdZw8QQqkPKZphUL0qFucoA0RRN5LUB1HGNOO6XDvAnRdCta2qtMIFcq1gJp9YHMA3L+sOo0wokVhi7gSd4WghkHYWNmojpMnSIGUB41rXwn3fLaM+D0cnU4uxVuEa4dg7xfQbAx4yqX3PK11EOQrYGgvo9OpTiOMIDw6nO9OfUf/6v0p71ZedZw8QwqkPCi/nTWzXvfh4OX7fLfviuo4IruSEwyz1orUAL/BqtMI1eycDG1lru6FA0tUpxHZ9Dj1MQF7AqhSoArvVHlHdZw8RQqkPMqvjAfv+JVkVsgZLkbHq44jsmPbZMPMpS5LwMpadRphCko1hnp9YdskuHtedRqRDfOPzufWo1tMbTgVa62c37lJCqQ8bFSbihRxdWD4ynBS0+RSvFm6vBsOLIbmgVBQLr2Lf2k+AZyLGm7cT0tVnUZkwaGoQ/wU8RODagyitEtp1XHyHCmQ8jAHWyvmdPPh+PUYvtp9SXUckVlJD2HNJ1DCH+r1U51GmBpbR8NaWDePwr75qtOITHqU8ojxe8dTs1BNelXupTpOniQFUh5Xq4Q7HzYuzedbznEmKk51HJEZf42HR/cM95to5VQWz1C8nqHdzPZpcPuU6jQiE+Yensv9xPtM9Z+KViPntwryUxcMbVGeUh75GL4ynORUGWozCxe2Gta6aTUF3EupTiNMWdOxUKCsYagtNVl1GpEBe2/sZdW5VQyvNRxvZ2/VcfIsKZAE9jZWzO1WnTNRD1mw/YLqOOJlHsfAmoFQuhnUfk91GmHqbOyh62LDFaTdc1SnES8RlxxH4L5AGhRuwBsV3lAdJ0+TAkkAUK2YCwOalWXh9gucuB6rOo54kZAxkBwPnRcYurkL8TJFahhWV981B24eU51GvMDMgzNJSElgsv9kNHJ+KyUFkkg34JWyVPRyYtjKMBJT0lTHEc9yZiOE/wJtZoBLMdVphDlpPMKwiOjqvpCSqDqNeIa/I/9m7cW1jKo7Cq98Xqrj5HlSIIl0NlZa5r7hy9V7CXy+9ZzqOOK/Ht2DdYOhfFuo/pbqNMLcWNlA1yVw/xLsmKY6jfiPB4kPmBQ6iSbFmtC5TGfVcQRSIIn/qOjlzJCW5fhq1yWOXL2vOo74t43DQZcCHb+QoTWRNZ5VoOkY2DsfIg+oTiP+JehAEGn6NCY0mCBDayZCCiTxlI8alaa6tyvDV4aTkCwLzJmEk3/AqdXQfi44eapOI8yZ3yAoVtvQnib5keo0Agi5HMLmK5sZV28cBR0Lqo4j/p8USOIp1lZa5nTz5VZsIrNCzqqOIx7ehg3DoXIXqPqa6jTC3FlZGxaQjLsJWyepTpPn3X18l6kHptKqRCvalGyjOo74FymQxDOVKZifUW0qsnzfFfZdvKs6Tt6l18P6IaC1hvafqU4jLIVHOWgxEQ4uhcu7VKfJs/R6PZP2TcJKY0VA/QAZWjMxUiCJ53rHryT1Srnz6arjPExMUR0nbwr/Fc5uNNx3lK+A6jTCktT9GEo0hOD+kCir6Kuw9uJadlzfQWCDQNzs3VTHEf8hBZJ4Lq1Ww5xuvjxISGbaxgjVcfKe2OuwaTT49oCK7VWnEZZGq4UuCyHhHvwVoDpNnhP1KIoZB2fQsXRHmhdvrjqOeAYpkMQLebs7Mq59JX49eI3tZ++ojpN36PWwdiDY5jOseSRETnArCa2nwtHv4fwW1WnyDL1eT+DeQBxtHBlVd5TqOOI5pEASL/VW3eI0KufB6D+OE5sgQ2254sh3cPFv6PwlOLiqTiMsWa13ocwrhoL88QPVafKEVedWEXorlEl+k3Cxc1EdRzyHFEjipTQaDbNe9yEhOY2J66QjeI67fxk2B0Ctd6BsC9VphKXTaKDTAkhOgE1yNSOnXXt4jTmH5/B6+ddpWLSh6jjiBaRAEhlS2MWBiR2rsPrYDUJORqmOY7l0OljT33BDdqupqtOIvMKlKLSdCcdXQMQ61Wkslk6vY/ze8bjbuzOi9gjVccRLSIEkMuzVmkVpUcmTcatPcC8+SXUcy3RgCVzdC50XgZ2T6jQiL/F9Eyq0g3VD4JEs7ZETfo74mSO3jzDFfwr5bPKpjiNeQgokkWEajYZpr1ZFp9cTEHwSvV6vOpJluXsetk2Cev2gVCPVaUReo9FAh3mg18H6oYaJAsJoLsde5oujX9CzUk/qeNVRHUdkgBRIIlMKOdkzpUtVNp2MYm34TdVxLEdaqqHLunNRaB6oOo3Iq5w8De1sItYa2tsIo0jVpRKwJwCvfF4MrjlYdRyRQVIgiUzr4FOEDj6FCVxzijtxiarjWIZ98+HmUUO3dVtH1WlEXlb1VajyqqG9zUO539AYlp9azsl7J5nqPxUHawfVcUQGSYEksmRK56rYWGkZ/ecJGWrLrtunYPs0QxNR77qq0whhuIpkZQtrB8lQWzade3COhWELeafKO1QvVF11HJEJUiCJLHHLZ8v0V6vx95k7rDpyXXUc85WabBhaK1AWmo1VnUYIA0d3Q3ub85sh7GfVacxWSloK4/aMo6RzSfpX7686jsgkKZBElrWs7MlrNYsxed1pbsQ8Vh3HPO2eA3dOG4bWrO1UpxHiHxXbge9bhnY3MddUpzFLX534igsPLjC14VRsrWxVxxGZJAWSyJbAjpVxsrdm1O/H0enkUnym3DwGu+ZA40+hSHXVaYR4WpvpYO8MawcY1ugSGXbq7imWHV/Ghz4fUqVAFdVxRBZIgSSyxcXBhpmv+bDnwl1+PnBVdRzzkZJoGFrzqgqNhqtOI8SzObhCpy/h0g44/I3qNGYjKS2JcXvGUd6tPB/6fKg6jsgiKZBEtjUuX5Ce9YozbeMZrt57pDqOedgxDe5fgi5LwMpGdRohnq9sc6j9HmwJNPybFS+18NhCIh9GEtQwCButnN/mSgokYRRj21XCw8mWEavCSZOhtheLPAB75xtuyvasrDqNEC/XcgrkKwjBn4AuTXUakxZ2J4zlp5bTv3p/yrmVUx1HZIMUSMIo8tlZM/t1Xw5ffcB3ey+rjmO6kh9BcF8oVtswrV8Ic2CXH7osgshQ2L9YdRqTlZCSwLg946hWsBrvVHlHdRyRTVIgCaOpX7oA7/qVYtbms1y481B1HNO0dRLE3TIMrWmtVKcRIuNKNoT6n8C2yRB9VnUak/TF0S+4k3CHIP8grOT8NntSIAmjGtmmAsXcHBi+MpzUNJn18oTLu+DgUmgxATzKqk4jROY1DwRXb8MEg7RU1WlMyoFbB/jlzC8MrjmYki4lVccRRiAFkjAqexsr5nbz5cSNWJbsvKg6julIjIPg/lCiIdT9WHUaIbLGxsFw9fNWGOz9XHUakxGfHE/g3kBqe9bmrUpvqY4jjEQKJGF0NYq70bdJGb7Ydp7TN+NUxzENfwXA4/vQZSFo5bQTZsy7DvgPhh0zIeqE6jQmYc7hOcQkxTDFfwpajZzflkLeSZEjBrcoR5mC+Rm2Mozk1Dw+1HZ+Cxz9HlpNBbeSqtMIkX1Nx4BHOcNQW2qy6jRK7b6+mz/O/8GIOiMo5lRMdRxhRFIgiRxhZ23FnG6+XLgTz5d/n1cdR53HD2DtQCjTHGq9ozqNEMZhbWdojxN9BnbNUp1GmdikWCbum4h/EX9eL/e66jjCyKRAEjmmalEXBr5SjkU7LhJ+LUZ1HDU2jYLkBMNqxBqN6jRCGE9hX2g8EnZ/BjeOqE6jxIyDM3ic+piJfhPRyPltcaRAEjnqk2ZlqFzYmeGrwklMyWMLzEWsg+MroO1McCmqOo0QxtdoGHhVg9X9ICVvNazednUb6y+tZ3S90Xjl81IdR+QAKZBEjrKx0jL3DV8i7yUw9688tHbKo7uwbghUaA++b6pOI0TOsLIxDLU9uAx/T1WdJtfcT7zP5P2TaebdjI6lO6qOI3KIFEgix5X3dGJ4q/J8vecyh67cVx0n5+n1sH4o6HXQcZ4MrQnLVqgSNBsHoQvhaqjqNDlOr9czdf9UdHodgQ0CZWjNgkmBJHLFB41KU7O4GyNWhZOQbOELzJ38AyLWQofPIH8h1WmEyHl+A6FYHQjuZ2inY8E2Xd7ElqtbCKgfgIeDh+o4IgdJgSRyhZVWw5xuvtyOS2TGpjOq4+Sch1GwYThUeRWqdFWdRojcobUyDLU9jIItE1SnyTF3Eu4QdCCINiXb0Lpka9VxRA6TAknkmlIe+RjdpiI/hF5l74W7quMYn14PaweBlS20n6s6jRC5q0AZaDkJDi2DSztUpzE6vV7PpNBJ2GhtGFdvnOo4IhcoL5AWLlxIyZIlsbe3p169ehw8ePCF28fExNC/f38KFy6MnZ0d5cuXZ+PGjbmUVmRX7wYlaVC6ACN/P05cYorqOMYV9jOc3wyd5oOju+o0QuS+Oh9CyUawZoChvY4FCb4QzK7ru5joNxFXe1fVcUQuyHKBtG3bNjp06ECZMmUoU6YMHTp0YOvWrZnax4oVKxg2bBgTJkzg6NGj+Pr60rp1a+7cufPM7ZOTk2nZsiVXrlzh999/5+zZsyxbtoyiRWUKtbnQajXMet2HmIRkpq4/rTqO8cRcg02joXpPqNBWdRoh1NBqofNCwwKpm8eqTmM0N+NvMvPQTDqX6UxT76aq44hckqUCadGiRbRp0wYnJycGDx7M4MGDcXZ2pl27dixcuDDD+/nss8/48MMPeffdd6lcuTJLlizB0dGRb7/99pnbf/vtt9y/f5/g4GD8/f0pWbIkTZo0wdfXNyvfhlDE292R8R0qs/Lwdf4+c1t1nOzT6WDtALB3hjbTVacRQi23EtA6CI79COc2q06TbTq9jsB9geS3yc+ouqNUxxG5SKPX6/WZfVGxYsUYPXo0AwYMeOLxhQsXMm3aNG7cuPHSfSQnJ+Po6Mjvv/9Oly5d0h/v06cPMTExrFmz5qnXtGvXDnd3dxwdHVmzZg0FCxbkrbfeYtSoUVhZWT3zOElJSSQlJaX//7i4OLy9vYmNjcXZ2TmD37EwNr1ez7vLD3HqZhxbhjbG1dFWdaSsO7gMNo6AXn9C2eaq0wihnl4PP78OUSfhk1CzHnL+7cxvBB0IYmmLpfgV9VMdR+Qi66y8KCYmhjZt2jz1eKtWrRg1KmMV9t27d0lLS8PT0/OJxz09PTlz5tmznC5dusTff/9Nz5492bhxIxcuXOCTTz4hJSWFCROePXNi+vTpTJo0KUOZRO7RaDTMeNWHVp/vZMLaU3zxZg3VkbLm/iXYEgi13zPb4kiv15OaauFLL5gxKysrtFrlt4tmjkZjaK+zqD5sGgmvfa06UZZExkXy2ZHPeKP8G1Ic5UFZKpA6derE6tWr+fTTT594fM2aNXTo0MEowZ5Fp9NRqFAhvvrqK6ysrKhVqxY3btxg9uzZzy2QxowZw7Bhw9L///+uIAn1vFzsmdS5CkNXhNOmihdtqxVWHSlzdGkQ/AnkKwgtp6hOkyWpqalER0eThQvJIhc5Ojri4uJiXosSOheBtrNh9UdQqSNU7qw6Uaak6dIYv3c87vbuDK89XHUcoUCWCqTKlSsTFBTEjh07aNCgAQD79+9n7969DB8+nPnz56dvO2jQoGfuw8PDAysrK27ffvIelNu3b+Pl9ey+NoULF8bGxuaJ4bRKlSoRFRVFcnIytrZPD9PY2dlhZ2eX6e9R5I4u1YsScjKKccEnqVPKHY/8ZvRe7V8MkfvhnQ1gl191mkzT6/XExMSg1Wpxc3Mzrz++eYReryc5OZm4OMOMMFdXV7WBMsvnDcOiqeuHQnE/yF9QdaIM+yniJ47dOca3rb/F0cZRdRyhQJbuQSpVqlTGdq7RcOnSpec+X69ePerWrcuXX34JGK4QFS9enAEDBjB69Ointh87diy//PILly5dSr/k/MUXXzBz5kxu3ryZoUxxcXG4uLjIPUgm5G58Eq0+30Xdku4s7lXTPP5QR5+FJY2gzgfQZprqNFmSlpbG7du3cXNzw8HBQXUc8QLx8fHExcXh5eVlfsNt8XcMQ20l/OCNH82i9c6lmEt0W9eN7hW7M7LOSNVxhCJZuoJ0+fJloxx82LBh9OnTh9q1a1O3bl3mzZvHo0ePePfddwHo3bs3RYsWZfp0w8ygfv36sWDBAgYPHszAgQM5f/4806ZNe+5VKmEePPLbMbVLVT75+Shrwm7SpYaJL9uQlgqr+4JrcWg+XnWaLNPpdADPneAgTMf/ro6npaWZX4GUvxC0/wxW9YETqwxXlUxYqi6VcXvGUSR/EQbVkL8teVmWCiRj6d69O9HR0QQGBhIVFUX16tUJCQlJv3E7MjLyiV8G3t7ebN68maFDh+Lj40PRokUZPHhwhm8MF6arXbXCdPItQuCakzQoUwBPZ3vVkZ5v7+dwKwze3wI25n/lxSyu2OVxZv8eVekCEa8bZnuWbATOpnu/4bcnv+X0/dP82PZH7K1N+PeQyHEZHmIbNmwYU6ZMIV++fE/c9Pwsn332mVHC5QQZYjNdMQnJtPx8F1WKOPPdO3VM849C1An4qpmhOWcL8+45lZKSQnR0NAULFsTGxkZ1HPECFvFeJdw3DLV5+UDPVSY51Hb2/lne3PAm71R5h8E1B6uOIxTL8BWkY8eOkZKSkv7fz2OSf9SEWXB1tGXma9V4b/lhVh6+Rvc6xVVHelJqsmFozaM8NH36HjkhxAs4ukPH+fBrd8MikjV7q070hJS0FMbuGUspl1L08+2nOo4wARkukLZv3/7M/xbCmF6p6MkbtYsxZX0E/mU9KOZmQrNHds2C6DPw4XawNqPZdhamadOmVK9enXnz5qmOIjKrQhuo3gtCxkLppob7+EzE4vDFXIq5xK8dfsXWyowXrhVGY2Z3+4m8IKBDZZztrRn5+3F0OhNZn+fGEdj9GTQZBYV9VKcRwny1mQb2LrCmv6FNjwk4EX2Cb09+y0e+H1HRvaLqOMJEZKlAevToEePHj8fPz4+yZctSunTpJ76EyA5nextmve7Lvov3+HH/VdVxIOUxrO4HXtWg4VDVaYQwb/Yu0HkBXN4Fh9SvsJ2Ymsi4veOo4F6BD6p9oDqOMCFZmsX2wQcfsHPnTt5++20KFy4s9x0Jo2tYzoO365dgxqYzNC5fkFIe+dSF+XsqPLgCH+8EKzO9QdZCPXjwgMGDB7Nu3TqSkpJo0qQJ8+fPp1y5cuj1egoVKsTixYt5/fXXAahevTq3b9/m1q1bAOzZs4fmzZvz4MEDHB1NaDjX0pVpZlhDbOsEQ4ueAmWURVlwbAHXH15nZYeV2Gjl/Bb/yFKBtGnTJjZs2IC/v7+x8wiRbnTbiuw6H82IVeGs/LgBVloFhfjVUAhdCC0nQaFKuX/8XPY4OY2L0fG5ftwyBfPjYJv59Zjeeecdzp8/z9q1a3F2dmbUqFG0a9eO06dPY2NjQ+PGjdmxYwevv/46Dx48ICIiAgcHB86cOUPFihXZuXMnderUkeJIhRaT4MJWCO4H724Cbe6vx3X09lF+OP0DQ2sNpaxb2Vw/vjBtWSqQ3NzccHc33+7Mwjzks7NmTjdf3lgayjd7LvFR41z+lJn8yPDL27suNBiQu8dW5GJ0PB2+3JPrx10/sCFVi7pk6jX/K4z27t2Ln5+hkejPP/+Mt7c3wcHBdOvWjaZNm7J06VIAdu3aRY0aNfDy8mLHjh1UrFiRHTt20KRJE6N/PyID7PJDl8XwXTvDhxD/3F2UMSElgYC9AfgW9KV3ZdOaUSdMQ5YKpClTphAYGMj3338vn7xEjqpT0p0PGpZizl/naFahEOU8nXLv4FsmwMMo6PWHkk+3KpQpmJ/1AxsqOW5mRUREYG1tTb169dIfK1CgABUqVCAiIgKAJk2aMHjwYKKjo9m5cydNmzZNL5Def/999u3bx8iR0kpCmRJ+0KC/YRi7XCsolHs3SH9+5HOiE6JZ3GIxVnnk/BaZk+ECqUaNGk/ca3ThwgU8PT0pWbLkUwuXHT161HgJRZ43vFUF/j5zh+Grwvmjnx82Vrkw+fLSDji0zNCNXOH9EbnNwdYq01dyTFm1atVwd3dn586d7Ny5k6CgILy8vJg5cyaHDh0iJSUl/eqTUOSVADj/FwT3NaxOnwv3+e2/tZ/fzv7G6LqjKeFcIsePJ8xThgukLl265GAMIZ7P3saKuW9U57XF+1i84yKDmpfL2QMmxsKaAYaWCHVkVoupqlSpEqmpqRw4cCC9yLl37x5nz56lcuXKgGHh2kaNGrFmzRpOnTpFw4YNcXR0JCkpiaVLl1K7dm3y5VM4AUAY2vV0WQLftIA9n0OTnL2i9zD5IYF7A6nrVZceFXvk6LGEectwgTRhgnm3VRDmrbq3K/2alGH+tvM0r1SIKkVy8CrH5rHwOAbeWQjm1hg0DylXrhydO3fmww8/ZOnSpTg5OTF69GiKFi1K586d07dr2rQpw4cPp3bt2uTPbxjKa9y4MT///DOffvqpqvji34rVgobDYOdMKN8mR9cam31oNrFJsXzX5ju0Gjm/xfNl6V/HtWvXuH79evr/P3jwIEOGDOGrr74yWjAh/mtQ83KULZSf4SvDSUpNy5mDnNsMx36C1kHgJpfeTd13331HrVq16NChAw0aNECv17Nx48Ynhv2bNGlCWloaTZs2TX+sadOmTz0mFGsyCgpWNLTzSU3KkUPsur6L1RdWM7LOSIrmL5ojxxCWI8PNav+tUaNGfPTRR7z99ttERUVRvnx5qlatyvnz5xk4cCCBgYE5kdUopFmteTt9M47OC/fwUePSfNrayDd0mkEzTWOyiAaoeUSeea/+1wzafxA0N+7fkdikWLqs6UJF94osar5I1u8TL5WlK0gnT56kbt26AKxcuZJq1aqxb98+fv75Z5YvX27MfEI8oXIRZwY3L8fiHRc5FvnAuDvfNBJSE6HTlxZfHAlhkryqGa4k7fkcrh826q6nHZhGUloSExtMlOJIZEiWCqSUlBTs7AzNOrdu3UqnTp0AqFixYvoKtULklL5NylCtqAvDV4WTmGKkobbTa+DEKmg3B5wLG2efQojMazgUClc3DLWlPDbKLrdc3cLGyxsZU3cMnvk8jbJPYfmyVCBVqVKFJUuWsHv3brZs2UKbNm0AuHnzJgUKFDBqQCH+y9pKy9w3fLn+4DGzN5/N/g7jo2H9UKjYAap1y/7+hBBZZ2UNXZdATCRsm5Lt3d17fI8poVNoXrw5HUp3MEJAkVdkqUCaOXMmS5cupWnTpvTo0QNfX18A1q5dmz70JkROKlvIiU9bVeDbvZc5cOle1nek18P6IYb/7jBPhtaEMAUFK0Dz8bB/EVzZm+Xd6PV6puw3FFnj64+XoTWRKZleSVuv11O6dGkiIyNJTU3Fzc0t/bmPPvpIVtYWuea9hqXYfCqKEb+HEzK4MfnssrAw/IlVcGY9vPED5C9o/JBCiKyp/wlErDe0++m3z9CaJJM2XN7AtshtzG0ylwIOMrohMifTV5D0ej1ly5YlKirqieIIoGTJkhQqVMho4YR4ESuthjndfLn7MJnpmyIyv4O4m7BxhGFYrXLnl28vhMg9WivosggeRcOWzM9ou/3oNtMOTKNtqba0KtkqBwIKS5fpAkmr1VKuXDnu3cvGsIYQRlLSIx9j2lXkp/2R7D4fnfEX6vWwdhBYO0DbWTkXUAiRdQXKQMvJcPgbuPh3hl+m1+uZGDoROys7xtUbl4MBhSXL0j1IM2bM4NNPP+XkyZPGziNEpvWqVwL/sgUY+ftx4hJTMvaioz/AhS3QaT44uudsQCFE1tV+H0o1MbT/SYzN0Ev+PP8ne27sYZLfJFzsLKe3oMhdWSqQevfuzcGDB/H19cXBwQF3d/cnvoTITVqthlmv+/IwMZXJ606//AUPrhraidToBeVb53xAIUTWabXQeSEkxkHImJdufiP+BrMOzaJr2a40LtY4FwIKS5WFu1ph3rx5Ro4hRPYUdXUgsENlRv5xnDZVvGhR+Tlrneh0sKY/OLhB6+m5G1IIkTWu3tBmOqwdAJU6QoW2z9xMp9cRuDcQZztnPq0jffZE9mSpQOrTp4+xcwiRbd1qF2PTyVuM/vMEW0q44ZbP9umNDn0NV3ZD7zVgL61mhDAbNXpBxFrDvYP9DzxzaPy3M79xMOogX7X8CidbJwUhhSXJcivjixcvEhAQQI8ePbhz5w4AmzZt4tSpU0YLJ0RmaDQaZrzmQ0qajsC1z/h3eO8ibJ0AdT6E0k1zPZ8wX2lpaeh0OtUx8jaNBjrOh7Rkw+zT/7gad5XPj3xO9wrdaVCkgYKAwtJkqUDauXMn1apV48CBA/z555/Ex8cDEB4ezoQJE4waUIjM8HS2Z3LnKqwLv8mG4/9qe6NLM6ynkt8TWk5SF1AYRUhICA0bNsTV1ZUCBQrQoUMHLl68CICfnx+jRo16Yvvo6GhsbGzYtWsXAElJSYwYMYKiRYuSL18+6tWrx44dO9K3X758Oa6urqxdu5bKlStjZ2dHZGQkhw4domXLlnh4eODi4kKTJk04evToE8c6c+YMDRs2xN7ensqVK7N161Y0Gg3BwcHp21y7do033ngDV1dX3N3d6dy5M1euXMmRn5VFcS5saAd08g84tTr94TRdGgF7AijoWJBhtYYpDCgsSZaG2EaPHs3UqVMZNmwYTk7/XMZ85ZVXWLBggdHCCZEVnXyLEHIyioDgE9Qt5U5BJzsIXQjXDsK7m8A2n+qIpis5Ae6ey/3jepQH24wvMvvo0SOGDRuGj48P8fHxBAYG0rVrV8LCwujZsyezZs1ixowZ6Ssnr1ixgiJFitCoUSMABgwYwOnTp/ntt98oUqQIq1evpk2bNpw4cYJy5coBkJCQwMyZM/n6668pUKAAhQoV4tKlS/Tp04cvv/wSvV7P3LlzadeuHefPn8fJyYm0tDS6dOlC8eLFOXDgAA8fPmT48OFPZE9JSaF169Y0aNCA3bt3Y21tzdSpU2nTpg3Hjx/H1vYZQ8PiH9VeNwy1rR8GJfwhfyF+OP0D4dHhLG+zHEcbWaxYGIdGr9frM/ui/Pnzc+LECUqVKoWTkxPh4eGULl2aK1euULFiRRITE3Miq1HExcXh4uJCbGwszs5yD4qluhefRKvPd1GzhBtftcmHZmkTqPshtA5SHc1kpKSkEB0dTcGCBbGxsTE8eDMMvmqS+2E+2glFqmf55Xfv3qVgwYKcOHECT09PihQpwt9//51eEPn5+dG4cWNmzJhBZGRkejeAIkWKpO+jRYsW1K1bl2nTprF8+XLeffddwsLC0lspPYtOp8PV1ZVffvmFDh06EBISQseOHbl27RpeXl6AoaF3y5YtWb16NV26dOGnn35i6tSpREREpBdwycnJuLq6EhwcTKtWTy9q+Mz3Ki97dBcW1gPvelxoM4k31nfnrYpvMaLO00NvQmRVlq4gubq6cuvWLUqVKvXE48eOHaNo0aJGCSZEdhTIb0dQ16oM+OkgMfdn4uZWEl4ZrzqW6fMobyhWVBw3E86fP09gYCAHDhzg7t276fcHRUZGUrVqVVq1asXPP/9Mo0aNuHz5MqGhoSxduhSAEydOkJaWRvnyTx4zKSnpiWbbtra2+Pj4PLHN7du3CQgIYMeOHdy5c4e0tDQSEhKIjIwE4OzZs3h7e6cXR8BT/SnDw8O5cOHCE1ffARITE9OHCcVL5POADp+TsvJtxllFU8ypGANqDFCdSliYLBVIb775JqNGjWLVqlVoNBp0Oh179+5lxIgR9O7d29gZhciSNlULM7/YDpzuRnC3xwY8bOxVRzJ9to7ZupKTWzp27EiJEiVYtmwZRYoUQafTUbVqVZKTkwHo2bMngwYN4ssvv+SXX36hWrVqVKtWDYD4+HisrKw4cuQIVlZWT+w3f/5/+n05ODg81dy0T58+3Lt3jy+++IISJUpgZ2dHgwYN0o+bEfHx8dSqVYuff/75qecKFpR+gBlWuRPfVPDjbMI1fqw7H3trOb+FcWWpQJo2bRr9+/fH29ubtLQ0KleuTFpaGm+99RYBAQHGzihE1tw6Ttv7P/Cd9lV27LXm+/J66eZtAe7du8fZs2dZtmxZ+hDanj17ntimc+fOfPTRR4SEhPDLL7888cGtRo0apKWlcefOnfTXZ9TevXtZtGgR7dq1Aww3W9+9ezf9+QoVKnDt2jVu376Np6dhLa5Dhw49sY+aNWuyYsUKChUqJMP82RBxL4KlKbd477GOarsXQIlmhpluQhhJlmax2drasmzZMi5evMj69ev56aefOHPmDD/++ONTn8iEUCI1CVb3RVOwEqVfn8Suc9H8evCa6lTCCNzc3ChQoABfffUVFy5c4O+//2bYsCdnLuXLl48uXbowfvx4IiIi6NGjR/pz5cuXp2fPnvTu3Zs///yTy5cvc/DgQaZPn86GDRteeOxy5crx448/EhERwYEDB+jZsycODg7pz7ds2ZIyZcrQp08fjh8/zt69e9M/NP6vOO/ZsyceHh507tyZ3bt3c/nyZXbs2MGgQYO4fv26sX5MFi05LZlxe8dR2rUM/V6ZCxe3wZHlqmMJC5PldZAAihcvTtu2benWrVv6zA8hTMLOmYbZWF0X07RyMd6s403QhtNcu5+gOpnIJq1Wy2+//caRI0eoWrUqQ4cOZfbs2U9t17NnT8LDw2nUqBHFixd/4rnvvvuO3r17M3z4cCpUqECXLl04dOjQU9v91zfffMODBw+oWbMmb7/9NoMGDaJQoULpz1tZWREcHEx8fDx16tThgw8+YNw4Q7NUe3vDEJCjoyO7du2iePHivPrqq1SqVIn333+fxMREuaKUQYvDF3M59jLTGk7DpkJbqNkb/gqAB1dURxMWJEuz2MDwi+Lzzz/n/PnzgOGT1ZAhQ/jggw+MGtDYZBZbHnD9MHzTEpqNhcaGdgMPE1NoM283xdwc+PXD+mi1cileZkbljr1799KwYUMuXLhAmTJlsrQPea/+cTz6OG9vepv+1fvzkc9HhgcT42CxH7iWgD7rDP3bhMimLP0rCgwMZPDgwXTs2JFVq1axatUqOnbsyNChQwkMDDR2RiEyLuUxrO4LhauD/9D0h53sbZj9ug8HLt/n+9AryuIJy7d69Wq2bNnClStX2Lp1Kx999BH+/v5ZLo7EPxJTExm3ZxyV3SvzXtX3/nnC3tnQ0PbqHjj4lbqAwqJk6SbtxYsXs2zZsifG9Tt16oSPjw8DBw5k8uTJRgsoRKZsmwIxkdB3N1g9+c/br6wHfRqUYGbIGZqUL0jpgvmfsxMhsu7hw4eMGjWKyMhIPDw8aNGiBXPnzlUdyyLMPzafm/E3WdVxFdba//z5Kt0E6n4EWydC2RbgUVZJRmE5snQFKSUlhdq1az/1eK1atUhNTc12KCGy5Mpe2L8ImgdCwQrP3GRU24p4OdszfFU4abosjS4L8UK9e/fm3LlzJCYmcv36dZYvX/7E+koiaw5HHean0z8xqOYgSruWfvZGLSYa2pEE9zW0FxIiG7JUIL399tssXrz4qce/+uorevbsme1QQmRaUryh11rx+lC/33M3c7S1Zk43X8KuxfDVrku5GFAIkVUJKQkE7A2gRqEa9KrU6/kb2uaDLosN9yHum597AYVFyvAQ27+n0Wo0Gr7++mv++usv6tevD8CBAweIjIyUhSKFGlsC4VE09A4G7YuXmqhd0p2PGpXm8y3neKViISp4Ob1weyGEWnMPz+V+4n2WtVyG1UvOb4rXB7+BsH0alGsNnpVzJ6SwOBmexdasWbOM7VCj4e+//85WqJwks9gs0MW/4ceuhi7fdT/M0EsSU9Lo+OUebK21BPf3x8Yq7816kZlR5iMvv1f7buzj460fM67eON6s+GbGXpSSaOgpaGULH/4NVnnrZyaMI8vT/M2VFEgWJjEWFjUAj3LQa3Wmpvcevx5D10X7GPhKWYa0yFwvMEuQl//ompu8+l7FJcfx6ppXKelSkq9afoVWk4kPMjeOwtctoMlIaDo650IKi5X3PjYLyxIyBpIeQqcFmV77xKeYK/2blmHB3xc4eSM2hwIKIbJq1sFZxKfEM8VvSuaKI4CiNaHRcNg1G26G5Ug+YdmyNM0/MTGRL7/8ku3bt3Pnzp30Ttr/c/ToUaOEE+KFzm6CsJ8N65+4emdpFwNeKcfWiDsMWxnGuoENsbOWVjlCmILtkdtZc3ENk/0mUzh/4aztpPGncG6TYW20j3eCtZ1xQwqLlqUrSO+//z6zZs2iRIkSdOjQgc6dOz/xJUSOS7gPawdB+TZQPeszJ22ttXzW3ZfLdx/x+ZbzRgwockrTpk0ZMmTIc5/XaDQEBwdneH87duxAo9EQExOT7WzCOGISY5gUOonGxRrTpWyXrO/I2ha6LoV7F2DHdKPlE3lDlq4grV+/no0bN+Lv72/sPEJkzMYRkJYMHb/Idgfvil7ODGlRnrl/naVlZU9qlXAzUkihwq1bt3Bzk/fQnAUdCCJFl8LEBhPTm/xmmWcVaDYG/p4KFdqDdx3jhBQWL0tXkIoWLYqTk0yNFoqcWg0n/4D2c8HJyyi7/LhxaaoVc2XEqnAeJ8sCc+bMy8sLOzsZSjFXIVdCCLkSwrh64yjoWNA4O/UbDEVqGBaQTJaG1SJjslQgzZ07l1GjRnH16lVj5xHixeLvwPphULkzVH3NaLu1ttIyt5svN2MeM2vzGaPtV+QMnU7HyJEjcXd3x8vLi4kTJ6Y/998htn379lG9enXs7e2pXbs2wcHBaDQawsLCntjnkSNHqF27No6Ojvj5+XH27Nnc+WZEuruP7xK0P4iWJVrStlRb4+3Yyhq6LIHY67BNWmGJjMnSEFvt2rVJTEykdOnSODo6PjXt9P79+0YJJ8QT9HpYNwQ0Wmj/WbaH1v6rbKH8fNq6AlM3RNCqshcNyuS99hCPUx9zOfZyrh+3lEspHKwdMrz9999/z7Bhwzhw4AChoaG88847+Pv707Jlyye2i4uLo2PHjrRr145ffvmFq1evPvf+pXHjxjF37lwKFixI3759ee+999i7d292vi2RCXq9nkmhk9BqtATUD8j+0Np/FSxvaEO0eSxUbA+lGhl3/8LiZKlA6tGjBzdu3GDatGl4enoa/x+yEM9yfAWc3QDdf4Z8HjlyiPf8S/HX6dt8+ns4IUMak98uS6eI2boce5nu67vn+nFXdFhB5QIZX/HYx8eHCRMmAFCuXDkWLFjAtm3bniqQfvnlFzQaDcuWLcPe3p7KlStz48YNPvzw6QVFg4KCaNKkCQCjR4+mffv2JCYmYm9vn43vTGTUukvr2HFtB/OazsPd3j1nDlKvH5zZAGs+gX77wE5uFRHPl6Xf/vv27SM0NBRfX19j5xHi2WJvwMaR4NMdKnXIscNotRrmvO5Lmy92EbQhgumvVsuxY5miUi6lWNFhhZLjZoaPj88T/79w4cLcuXPnqe3Onj2Lj4/PE0VO3bp1X7rPwoUN08rv3LlD8eLFM5VNZF7UoyhmHJhBh9IdaF6iec4dSKs1LAuy2B/+Gg8d5+XcsYTZy1KBVLFiRR4/fmzsLEI8m14PaweCrSO0nZnjhytewJGx7SoREHySNlW9aFLeSDeKmgEHa4dMXclR5b/D+hqN5qn12LKzz/9dFc/uPsXL6fV6JuybgIO1A6Pr5sKK1+6loNUU2DDM8GGrbIucP6YwS1m6SXvGjBkMHz6cHTt2cO/ePeLi4p74EsKojiyHi9sMq2U75M707Z71itOonAejfj9O7OOUXDmmML4KFSpw4sQJkpKS0h87dOiQwkTiv34//zv7bu5jot9EXOxccuegtd+D0s1gzUB4HJM7xxRmJ0sFUps2bQgNDaV58+YUKlQINzc33NzccHV1lfVHhHE9uAJ/BUDNPlAu9z7paTQaZr7mw6OkVCatO5VrxxXG9dZbb6HT6fjoo4+IiIhg8+bNzJkzB0DunTQB1x9eZ/ah2bxW7jUaFcvFm6Y1Gui8AJLjIUT6tIlny9IQ2/bt242dQ4in6XQQ3B8c3KF1UK4fvoirA4EdK/Pp78dpU8WLVlWMs+aSyD3Ozs6sW7eOfv36Ub16dapVq0ZgYCBvvfWW3HytmE6vY/ze8bjZuTGi9ojcD+BSDNrMMNywXamjYWabEP+i0ev1etUhclNcXBwuLi7Exsbi7OysOo54kf1LIGQU9FkHpRoriaDX6/nwh8OEXYvhr6FNcM9nqyRHTsirHeJ//vln3n33XWJjY3FwyPjSAipZ4nv10+mfmHloJt+0+oa6hZ9943yO0+vh1zfhxhH45ADky3tLe4jny9IQG8Du3bvp1asXfn5+3LhxA4Aff/yRPXv2GC2cyMPuXoCtE6Hux8qKIzAMw0x7tRqpOj3j15xUlkNk3Q8//MCePXu4fPkywcHBjBo1ijfeeMNsiiNLdDn2MvOOzuOtim+pK47AMNTW8QvQpcLG4epyCJOUpQLpjz/+oHXr1jg4OHD06NH0GyBjY2OZNm2aUQOKPEiXZmgJ4FwYWkxQnYZCTvZM6VyVDcdvsS78puo4IpOioqLo1asXlSpVYujQoXTr1o2vvvpKdaw8K02XRsDeADwdPRlcc7DqOIZ2Re3m/NPCSIj/l6UCaerUqSxZsoRly5Y9cbnX39+fo0ePGi2cyKP2zTdc8u6yBGzzqU4DQEffIrSvVpjxa05y52Gi6jgiE0aOHMmVK1dITEzk8uXLfP755zg6OqqOlWctP7Wck3dPEtQwCEcbE3kfqr4GlbvAhuHw8LbqNMJEZKlAOnv2LI0bPz3s4eLiQkxMTHYzibzs9mnYPg0aDIDi9VSnecKULlWx1moY++cJ8tite0IYxfkH51kYtpA+lftQvVB11XH+odEY2hdprWHdYMO9SSLPy1KB5OXlxYULF556fM+ePZQuXTrboUQelZYCqz8G99LQbJzqNE9xz2fLtK7V2Bpxhz+O3lAdx2ik2DN9lvAepehSGLdnHMWditO/Rn/VcZ6WrwB0mAfnNkH4r6rTCBOQpWn+H374IYMHD+bbb79Fo9Fw8+ZNQkNDGTFiBOPHjzd2RpFX7J4Lt0/Bh9vAxjSnYLeq4sWrNYsyae0p/MoUoIir+d7oa2VlhUaj4eHDhzg5Ocm6QCZIr9eTlpZGXFwcGo0Ga2vz7Q247Pgyzj04x8/tfsbOyk51nGer1AF83oRNowyTQ1yKqU4kFMrSNH+9Xs+0adOYPn06CQkJANjZ2TFixAimTJli9JDGJNP8TdTNMPi6OTQaDs3Gqk7zQrGPU2j9+S7Keebnh/fqmnVhkZSUxP379y3iCoUls7W1xdXV1WwLpFP3TtFrQy/er/Y+A2oMUB3nxR4/gEV+ULACvL3aMPwm8qRsrYOUnJzMhQsXiI+Pp3LlyuTPn9+Y2XKEFEgmKDUJljYBK2v44G+wNv21hnaei6bPtweZ2qUqveqXUB0nW3Q6HWlpaapjiOfQarVotVqzLcST05Lpvr471lprfmn3CzZWZrCO0/mt8PNrhvuS6ryvOo1QJFMfR957770Mbfftt99mKsTChQuZPXs2UVFR+Pr68uWXXz634/a//fbbb/To0YPOnTsTHBycqWMKE7J9Gty7AB/vNIviCKBJ+YL0qFucaRsjaFyuIMULmMhsnCz43x9gIXLCwrCFXIm7wooOK8yjOAJDW6Na78Bf46HMK4YGtyLPydRvxeXLl7N9+3ZiYmJ48ODBc78yY8WKFQwbNowJEyZw9OhRfH19ad26NXfu3Hnh665cucKIESNo1CgX+/cI47t20DCtv9kY8KyiOk2mjGtfCfd8toz4PRydToaohPivsDthLD+1nP7V+1PerbzqOJnTaqrhxu01/Q1tj0Sek6khtv79+/Prr79SokQJ3n33XXr16oW7u3u2AtSrV486deqwYMECwHC539vbm4EDBzJ69LObCKalpdG4cWPee+89du/eTUxMzHOvICUlJT3RyTsuLg5vb28ZYjMFyQmwpCE4uMF7mw1DbGYm9OI9eizbz/gOlXm/oXzKFOJ/Hqc+ptu6bjjbOvND2x+w1prf+c3l3fB9B2g9HRp8ojqNyGWZuoK0cOFCbt26xciRI1m3bh3e3t688cYbbN68OUs3eSYnJ3PkyBFatPinS7tWq6VFixaEhoY+93WTJ0+mUKFCvP/+y8eGp0+fjouLS/qXt7d3pnOKHLJtMsTdgK5LzLI4AmhQpgDv+pdkVsgZLkbHq44jhMn44ugXRD2KYmrDqeZZHAGUagT1+sK2SXD3vOo0Ipdl+sYDOzs7evTowZYtWzh9+jRVqlThk08+oWTJksTHZ+4PxN27d0lLS8PT0/OJxz09PYmKinrma/bs2cM333zDsmXLMnSMMWPGEBsbm/517dq1TGUUOeTybjiwGJpPAI9yqtNky8jWFSni6sDwleGkpsmleCEO3jrIzxE/M6jGIEq7mPnaeM0ngHNRWN0X0lJVpxG5KFt3Zv5vZsX/1urIaQ8fPuTtt99m2bJleHh4ZOg1dnZ2ODs7P/ElFEt6CGs+gRL+hk9nZs7B1oo53Xw5fj2GpbsuqY4jhFKPUh4RuC+QWp616FW5l+o42WfraLjKffMo7PtCdRqRizJdICUlJfHrr7/SsmVLypcvz4kTJ1iwYAGRkZGZnubv4eGBlZUVt28/2fvm9u3beHl5PbX9xYsXuXLlCh07dsTa2hpra2t++OEH1q5di7W1NRcvXszstyNU+CsAHt2DzgvBQmZP1SrhxkeNyzBv6znORMWpjiOEMnMOz+F+4n2m+E9Bq7GM8xvvuuA3CLZPNyxmK/KETP3r/eSTTyhcuDAzZsygQ4cOXLt2jVWrVtGuXbssTRO2tbWlVq1abNu2Lf0xnU7Htm3baNCgwVPbV6xYkRMnThAWFpb+1alTJ5o1a0ZYWJjcX2QOLmyFI8uh1RSLmzo7tGU5SnnkY9iKcJJTZahN5D17buzh93O/M6L2CLydLOz3cbOxUKCsoR1SarLqNCIXZGoWm1arpXjx4tSoUeOFi5b9+eefGQ6wYsUK+vTpw9KlS6lbty7z5s1j5cqVnDlzBk9PT3r37k3RokWZPn36M1//zjvvvHAW23/JQpEKPY6BRQ0seoXakzdi6bJwL580K8uwlmY2rVmIbIhNiuXVta9SxqUMS1suNduFLV/o5jH4uoVZrPgvsi9TUwt69+5t9H/03bt3Jzo6msDAQKKioqhevTohISHpN25HRkbKInaWImQ0JMdD5wUWWRwBVC3qwoBXyvLl3xdoUakQPsVcVUcSIlfMPDiThJQEJvtPtsziCKBIDWg0AnbNhvJtoGhN1YlEDspWqxFzJFeQFDmzAX57C7oshupvqU6To1LSdHRdtJekFB3rBjbE3sZKdSQhctS2yG0M2T6EKf5T6FK2i+o4OSstBZa9AmnJ8NFOk22sLbJPLs2InPfoHqwbDOXbgm8P1WlynI2VlrndqnP1XgKfbzmnOo4QOepB4gMmh06mabGmdC7TWXWcnGdlA12Xwv1LsD1IdRqRg6RAEjlvwzDQpULHLyx2aO2/Kng5MbRleb7afYkjV++rjiNEjtDr9UzZP4U0fRoT/CZY7tDaf3lWNtyDtO9LiDygOo3IIVIgiZx18g84HQzt54KT50s3tyQfNS5NdW9Xhq8MJyFZFpgTlifkSghbrm4hoF4AHg4ZW5vOYvgNgmK1IbgvJD9SnUbkACmQRM55eBs2DIcqXaHqa6rT5DorrYa53XyJiktkVshZ1XGEMKrohGiCDgTRqkQr2pRqozpO7tNaQZclEHcLtk5SnUbkACmQRM7Q62HdINBaQ7u5qtMoU7pgfka1qcjyfVfYd+Gu6jhCGIVer2dS6CSsNFYE1A9QHUcdj7LQYgIcXAqXdqpOI4xMCiSRM8J+gXMh0HE+5CugOo1SfRqUpH5pdz79/TgPE1NUxxEi29ZcXMPO6zuZ0GACbvZuquOoVfdjKNEQ1gyARFlF35JIgSSML/a6Yc0j3x5QsZ3qNMpptRpmv+5LTEIyQRsiVMcRIluiHkUx8+BMOpXpxCvFX1EdRz2tFroshMf34a9xqtMII5ICSRiXXm/4JGWbH9rMUJ3GZHi7OzKufWV+O3SN7WfvqI4jRJbo9XoC9wbiaOPIqLqjVMcxHW4lodVUOPoDnN+iOo0wEimQhHEd/hYubYfOX4KDq+o0JqVHXW8aly/I6D+OE5sgQ23C/Kw6t4rQW6FM9puMs60stPuEWu9AmeawdiA8fqA6jTACKZCE8dy/DH+Nh1rvQtkWqtOYHI1Gw8zXqpGQnMbEddIRXJiXaw+vMefwHF4v/zr+Rf1VxzE9Gg10+hKSE2CTXF2zBFIgCePQ6SD4E8MN2a2mqE5jsgq7ODCpUxVWH7tByMko1XGEyBCdXkfAngDc7d0ZUXuE6jimy6UotJ0Jx1dAxDrVaUQ2SYEkjOPAYojcZ+i1ZuekOo1J61qjKC0rezJu9QnuxSepjiPES/10+ieO3jnKFP8p5LPJpzqOafN9Eyq0h3VD4JEs7WHOpEAS2Rd9DrZNhnr9oGRD1WlMnkajYVrXauj0egKCT5LH+kULM3Mp9hLzj82nV6Ve1PGqozqO6dNooOM80Otg/VDDxBVhlqRAEtmTlmpYat+lGDQPVJ3GbBR0smNql2psOhnF2vCbquMI8UypulQC9gTglc+LQTUHqY5jPvIXgg6fQcRaQ7slYZakQBLZs+8LuHnMsOS+raPqNGalvU9hOvoWIXDNKW7HJaqOI8RTlp9azql7p5jqPxUHawfVccxLla5Q5VVDu6W4W6rTiCyQAklkXdRJ2D4d/AeDt1x6z4rJnapga61lzJ8nZKhNmJSz98+yMGwh71R5h+qFqquOY57azwUrW1g3WIbazJAUSCJrUpMNQ2se5aDpGNVpzJZbPlumd63G32fusOrwddVxhAAgJS2FgL0BlHQuSf/q/VXHMV+O7tBpPpzfDMd+Up1GZJIUSCJrds2GOxGGWWvWdqrTmLUWlT15vVYxJq8/zfUHCarjCMHS40u58OACQQ2DsLWyVR3HvFVoC9V7QsgYiIlUnUZkghRIIvNuHIXdc6Hxp1Ckuuo0FiGwY2Wc7K0Z9cdxdDq5FC/UOXX3FF+f+JqPfD6icoHKquNYhjbTwd7Z0IZJp1OdRmSQFEgic1ISYXVf8KoKjYarTmMxnO1tmPmaD3sv3OPnA1dVxxF5VFJaEmP3jKW8W3k+8PlAdRzLYe9iWGX78k44/I3qNCKDpEASmbM9CB5chq5LwcpGdRqL0rh8QXrWK860jWe4cveR6jgiD1p4bCHXHl4jqGEQNlo5v42qbHOo/R5sCYR7F1WnERkgBZLIuMj9sO9LaDYOClVSncYijW1XCQ8nWz79PZw0GWoTuejYnWMsP7Wc/tX7U86tnOo4lqnlFMhXENb0B12a6jTiJaRAEhmT/AiC+0GxOuA3UHUai5XPzpo5r/ty+OoDvt1zWXUckUckpCQQsCeAagWr8U6Vd1THsVx2+Q0TWyL3w/5FqtOIl5ACSWTM1kmGxc66LAatleo0Fq1e6QK851+K2X+d5cKdh6rjiDxg3tF53Em4Q5B/EFZyfueskv5Q/xPYNgWiz6pOI15ACiTxcpd2wsGl0GIieJRVnSZP+LR1BYq5OTB8ZTipaTLrReScA7cO8OuZXxlSawglXUqqjpM3NB8PrsUNE17SUlWnEc8hBZJ4scQ4w9TUko2g7keq0+QZ9jZWzO3my4kbsSzZKTd0ipwRnxzP+L3jqeNVhx4Ve6iOk3fYOEDXJXArDPZ+rjqNeA4pkMSL/TUOHt+HzgtBK/9cclON4m70bVKGL7ad5/TNONVxhAWac3gOsUmxTPabjFYj53euKlYb/IfAjpkQdUJ1GvEMckaI5zu/BY7+AK2DwK2E6jR50uAW5ShTMD/DVoaRnCpDbcJ4dl3fxR/n/2BEnREUcyqmOk7e1HQ0eJQ3DLWlJqtOI/5DCiTxbI8fwNqBULYF1OyjOk2eZWdtxdw3fLlwJ575286rjiMsRGxSLBP3TcS/iD+vl3tddZy8y9rOMNQWfQZ2zVKdRvyHFEji2TaNgpQEw+qvGo3qNHlalSIuDGpejsU7LxJ2LUZ1HGEBph+cTmJqIhP9JqKR81utwj7QZBTs/gxuHFGdRvyLFEjiaRHr4PgKaDsLnIuoTiOAfk3LULmwM8NXhpGYIgvMiazbenUrGy5tYEy9MXjl81IdRwA0HApe1WB1P0h5rDqN+H9SIIknPboL64ZAxQ7g0111GvH/bKy0zH3Dl2sPHjP3L1k7RWTN/cT7TNk/hWbezehQuoPqOOJ/rGwMQ20PrsDfU1WnEf9PCiTxD70e1g8FvQ46fC5DayamvKcTw1uW5+s9lzl4+b7qOMLM6PV6poROQafXEdggUIbWTE2hSvDKOAhdCFdDVacRSIEk/u3kHxCx1lAc5S+kOo14hg8alaZmcTdGrArnUZIsMCcybuPljWyN3EpA/QA8HDxUxxHP0mAAeNc1tHVKlobVqkmBJAzibsGG4VD1NajSRXUa8RxWWg1zuvly52EiMzadUR1HmIk7CXeYdmAabUu2pXXJ1qrjiOfRWhnaOT2Mgi0TVKfJ86RAEoahtXWDDVNO281RnUa8RCmPfIxpW4kf919lz/m7quMIE6fX65m4byK2VraMrTdWdRzxMgXKQMvJcGgZXNqhOk2eJgWSgGM/wfnN0HE+OLqrTiMy4O36JWhQugAjfw8nLjFFdRxhwoIvBLP7xm4mNJiAq72r6jgiI+p8YGjvtGYAJMaqTpNnSYGU18VEQsgYqN4LKrRRnUZkkFarYdbrPsQlpjJ1/WnVcYSJuhl/k5mHZtK5TGeaejdVHUdklFZraO/0OAY2y1U/VaRAyst0OsMnFHsXaDNNdRqRSd7ujgS0r8TKw9f5+8xt1XGEidHpdQTuDcTJ1olRdUepjiMyy62Eoc3TsZ/g3GbVafIkKZDyssPfwOWd0HmBoUgSZqd7HW+aVijIqD9OEJMgvZzEP1acXcGBqANM8puEk62T6jgiK2r2hrItDW2fEmRpj9wmBVJede8ibAmE2u9DmWaq04gs0mg0zHzNh6SUNCasPaU6jjARkXGRfH7kc7pX6I5fET/VcURWaTSGdk+pibBppOo0eY4USHmRLg3W9DesddRysuo0Ips8ne2Z3Lkqa8JusunELdVxhGJpujQC9gZQwL4Aw2oNUx1HZJdzYcPs4hOr4PQa1WnyFCmQ8qL9iyByv2G9Dbv8qtMII+hcvQitq3gyLvgkd+OTVMcRCv0U8RNhd8KY4j8FRxtH1XGEMVTrZmj/tH4oxEerTpNnSIGU10SfhW1ToEF/KCGX3i2FRqMhqGs1AMatPoFer1ecSKhwMeYi84/Op1flXtT2qq06jjAWjQY6zDP89/ohhrXrRI6TAikvSUuF1X0NsyNeCVCdRhiZR347grpUZfOp26wJu6k6jshlqbpUxu0ZR5H8RRhUY5DqOMLY8hc0tIE6s94w3CZynBRIecnez+FWGHRZAjYOqtOIHNC2WmE6Vy9C4JqTRMUmqo4jctE3J74h4n4EQQ2DsLe2Vx1H5ITKnQ3DbRtHQJx8CMppUiDlFVEnYMdMaDgUitVSnUbkoEmdqmBvY8XoP4/LUFseceb+GZYcX8J7Vd/Dp6CP6jgiJ7WdBdYOsHaQDLXlMCmQ8oLUZMPQWsEK0EQWjLN0ro62zHitGjvORrPi0DXVcUQOS0lLYdyecZRyKUU/336q44ic5ugOnebDhS1w9AfVaSyaFEh5wc6ZEH3GMGvN2k51GpELXqnoyRu1izFl/Wmu3U9QHUfkoMXhi7kUc4lpDadha2WrOo7IDeVbQ41ehjYkD66qTmOxpECydNePwJ7PocloKCyX3vOS8R0q4+poy8jfj6PTyaV4S3Qi+gTfnPyGj30/pqJ7RdVxRG5qPR0c3Axr2ul0qtNYJCmQLFnKYwjuayiMGg5VnUbkMid7G2a97kPopXv8uF8+ZVqaxNRExu0dR0X3irxf7X3VcURus3c2tIm6shsOfa06jUWSAsmS/T3VcPm1yxKwsladRijgX9aD3g1KMH1TBJfvPlIdRxjRl8e+5MbDGwT5B2GjtVEdR6hQuinU+dDQNureRdVpLI4USJbq6j4IXWhY76iQXHrPy0a3rYinsz0jVoWTJkNtFuHI7SP8ePpHBtQYQFm3sqrjCJVaTgInLwjuZ2gjJYxGCiRLlBRvOFm86xlWzBZ5mqOtNXO6+XI08gFf776kOo7IpoSUBAL2BOBb0JfelXurjiNUs81nmIBz7SCELlCdxqJIgWSJtk6A+DvQZRForVSnESagTkl3PmhYirl/nePc7Yeq44hs+OzIZ9x9fJepDadiJee3ACjRwPBh+O+pcCdCdRqLIQWSpbm43XDDXsvJUKCM6jTChAxvVYHiBRwZvjKclDSZ9WKOQm+GsuLsCobWGkoJ5xKq4whT8sp4cCtlWPMuLUV1GosgBZIlSYyFNQOgVGOoLbNaxJPsbayY282X07fiWLxDbug0Nw+THxK4L5C6XnV5s+KbquMIU2NjD10XG7om7PlcdRqLIAWSJdk81lAkdV4IWnlrxdN8vV35pGkZ5m87z8kbsarjiEyYdWgWD5MfMtl/MlqNnN/iGYrWgkbDDIsD3wpXncbsyVlmKc6GwLGfoM00cC2uOo0wYQNfKUc5TydGrAonKVVmvZiDndd2EnwhmE9rf0rR/EVVxxGmrPFIKFgJVveD1CTVacyaFEiWIOE+rBsE5VpBjbdVpxEmztZay9xuvlyMjueLredVxxEvEZMYw8TQiTQs2pBXy72qOo4wdda2hqG2u+dgxwzVacyaFEiWYOOnhk8KHeeDRqM6jTADlYs4M7h5OZbsvMixyAeq44gXmHZwGklpSUzym4RGzm+REV7VoOko2DsPrh9WncZsSYFk7k4Fw8nfod1scC6sOo0wI32blKFaUReGrwonMUWG2kzRX1f+YtPlTYytN5ZCjoVUxxHmxH8oFK5umNWW8lh1GrNkEgXSwoULKVmyJPb29tSrV4+DBw8+d9tly5bRqFEj3NzccHNzo0WLFi/c3qLFR8OGYVCpI1TrpjqNMDPWVlrmvuHL9QePmb35rOo44j/uPr7L1P1TaV68Oe1LtVcdR5gbK2vougRiImHbFNVpzJLyAmnFihUMGzaMCRMmcPToUXx9fWndujV37tx55vY7duygR48ebN++ndDQULy9vWnVqhU3btzI5eSK6fWwfojhv9t/LkNrIkvKFnJiZOsKfLv3Mgcu3VMdR/w/vV7PlFDDH7Xx9cfL0JrImoIVoPl42L8IruxVncbsaPR6vdLmTPXq1aNOnTosWGBYIl2n0+Ht7c3AgQMZPXr0S1+flpaGm5sbCxYsoHfvp5fdT0pKIinpnzv54+Li8Pb2JjY2FmdnZ+N9I7ktfAWs/gje+BEqd1KdRpixNJ2eN78KJSoukZDBjclnJ42NVVt3cR1j94zls6af0bJES9VxhDnTpcHy9hB3E/rtA7v8qhOZDaVXkJKTkzly5AgtWrRIf0yr1dKiRQtCQ0MztI+EhARSUlJwd3d/5vPTp0/HxcUl/cvb29so2ZWKuwmbPjUMq0lxJLLJSqthTjdf7j5MZtpGaVOg2u1Ht5l+YDrtSrWT4khkn9bK0HbqUTRsGa86jVlRWiDdvXuXtLQ0PD09n3jc09OTqKioDO1j1KhRFClS5Iki69/GjBlDbGxs+te1a9eynVspvR7WDgRrB2g7S3UaYSFKFMjH2HYV+flAJLvORauOk2fp9XomhE7A3tqesfXGqo4jLIV7aUP7qcPfwoVtqtOYDeX3IGXHjBkz+O2331i9ejX29vbP3MbOzg5nZ+cnvsza0R/gwlbo9CU4PvuqmRBZ0bNeCRqW9WDUH8eJfSy9nFT44/wf7L2xl4l+E3Gxc1EdR1iS2u9DqSaGD9iPY1SnMQtKCyQPDw+srKy4ffv2E4/fvn0bLy+vF752zpw5zJgxg7/++gsfH5+cjGk6Hlw1tBOp8TaUb6U6jbAwWq2Gma/7EJ+YypT1p1XHyXNuxN9g9qHZdC3blcbFGquOIyyNVmtoQ5UYZ/g7Il5KaYFka2tLrVq12Lbtn0t+Op2Obdu20aBBg+e+btasWUyZMoWQkBBq166dG1HV0+lgTX9wcIPW01SnERaqqKsD4ztW5vcj19ly+vbLXyCMQqfXMX7veFzsXBhZZ6TqOMJSuXpDm+kQ9jOc2ag6jclTPsQ2bNgwli1bxvfff09ERAT9+vXj0aNHvPvuuwD07t2bMWPGpG8/c+ZMxo8fz7fffkvJkiWJiooiKiqK+Ph4Vd9C7ji0DK7shs4LwN7MhwmFSetWqxjNKxZizJ8nePAoWXWcPOHXM79yKOoQk/0nk99WZhmJHFSjF5RrDesGG9pUiedSXiB1796dOXPmEBgYSPXq1QkLCyMkJCT9xu3IyEhu3bqVvv3ixYtJTk7m9ddfp3Dhwulfc+bMUfUt5Lx7F2HLBKjzIZRuqjqNsHAajYbpr1YjJU3H+DUnVcexeFdirzDvyDzerPAm9QvXVx1HWDqNBjrNh7Rk2DBcdRqTpnwdpNwWFxeHi4uL+ayDpEuDb9sYpmj22wu2+VQnEnnEmrAbDP4tjAVv1aCDTxHVcSxSmi6NPiF9uJ94n987/o6jjaPqSCKvOPE7/PE+vP4dVJUmyM+i/AqSeInQBXD9kGHJeCmORC7q5FuEdtW8GB98kuiHSS9/gci0709/z/Ho40z1nyrFkchdVV+DSp0MV5Hin925Iq+TAsmU3YmAv6eC3wAoLpfeRe7SaDRM6VwVrUbDmD9PkMcuNue4Cw8usODYAnpX7k1Nz5qq44i8RqOBDp+DRmu4H0nO76dIgWSq0lIMXZjdSkGzANVpRB5VIL8d016txtaI2/x5NI/1O8xBKboUxu4Zi7eTNwNrDlQdR+RV+Tyg4zw4uxHCf1OdxuRIgWSqdn8GUSeg62KwefYimELkhtZVvOhaoygT153iVuxj1XEswtcnvubcg3MENQzCzspOdRyRl1XqCD7dYdMoiJUPQf8mBZIpuhUOu2ZBo2FQtJbqNEIwsWMVHG2tGPn7cRlqy6bT907zVfhXvF/tfap6VFUdRwhoOxNsHWHtABlq+xcpkExNapJhaK1gJWgsC8YJ0+DiaMPM13zYff4uvx40836GCiWnJTNuzzjKuJahr09f1XGEMHBwM7Svuvg3HFmuOo3JkALJ1OyYAXfPG2atWduqTiNEuqYVCtGjrjdTN5zm2v0E1XHM0qKwRVyJu0JQwyBsrGxUxxHiH+VaQs3esHkcPLiiOo1JkALJlFw7BHvnQdPR4CWX3oXpGde+Mm6OtoxYFY5OJ5fiMyM8OpzvTn1HP99+VHCvoDqOEE9rFQSOBSC4v6G9VR4nBZKpSE6A4L5QpAb4D1GdRohnym9nzexuPhy4fJ/l+66ojmM2Hqc+JmBPAJXdK/Ne1fdUxxHi2eydoctCuLoHDi5VnUY5KZBMxd9TIPY6dFkCVtaq0wjxXH5lPHjHryQzQ85wMdrCeyAayfyj87kZf5OghkFYa+X8FiasVGOo+zFsnQR3L6hOo5QUSKbgyh7YvxheGQ8Fy6tOI8RLjWpTkSKuDoxYFU6aDLW90KGoQ/wU8RODag6itGtp1XGEeLkWE8C5sGFUQ5emOo0yUiCplhQPwZ9A8QZQv5/qNEJkiIOtFXO6+RB+LYavdl1SHcdkJaQkMH7veGoWqkmvSr1UxxEiY2zzGUYzbhyBffNVp1FGCiTVtow3NKLtshC0VqrTCJFhtUq482Hj0ny+5Rxnox6qjmOS5h6ey/3E+0z1n4qVnN/CnBSvBw0GwPZpcPu06jRKSIGk0oVtcPhbaDUF3OXSuzA/Q1uUp0QBR4atDCMlTWa9/Nu+G/tYeW4lw2oNw9vZW3UcITKv2TjD36bVHxvaX+UxUiCp8jgG1g6E0k2h9vuq0wiRJfY2Vnz2RnXORD1kwd95+4bOf4tLjiNwXyD1C9fnjQpvqI4jRNbY2BvW5Lt9CnbPVZ0m10mBpErIGEh6CJ0WGLoqC2GmqhVzoX+zsizcfoET12NVxzEJMw/O5FHKIyb7TUarkV+zwowVqQGNR8Cu2XAzTHWaXCVnrgpnNkL4L9BmOrjKpXdh/gY0K0t5TyeGrwojKTXvznoB2B65nbUX1zKyzkgK5y+sOo4Q2ddoBBSqZGiDlZqkOk2ukQIptyXch3WDoXwbqN5TdRohjMLWWstn3X25fPcRn285rzqOMjGJMUwKnUSTYk3oUraL6jhCGIe1LXRdCvcuGG7aziOkQMptG4ZDWjJ0/EKG1oRFqejlzJAW5flq10WOXH2gOo4SQQeCSNGlMKHBBDRyfgtL4lkFmo0xTPu/dlB1mlwhBVJuOvknnPoT2s8FJy/VaYQwuo8bl8anmCsjVoXzODlvDbWFXAkh5EoI4+qNo6BjQdVxhDA+v8FQpKZhqC3Z8htWS4GUW+LvGK4eVe4MVV9TnUaIHGFtpWXuG77cjHnMzJAzquPkmruP7xK0P4iWJVrStlRb1XGEyBlW1oZZbXE3YNtk1WlynBRIuUGvN9x3pLWC9p/J0JqwaGUK5mdkm4os33eFfRfvqo6T4/R6PZNCJ6HVaAmoHyBDa8KyeZSD5hPgwGK4vFt1mhwlBVJuCP8Nzm6EDvMgn4fqNELkuHf9SlK3lDsjfz9OfFKq6jg5at2ldey4toPABoG427urjiNEzqvXF0r4w5pPDMvVWCgpkHJa7A3YNAp83oRKHVSnESJXaLUa5rzuy/1HyQRtiFAdJ8dEPYpixoEZdCjdgebFm6uOI0Tu0Gqh80J4dA/+ClCdJsdIgZST9HpYOwBsHaHtDNVphMhVxQs4MrZdJX49GMnOc9Gq4xidXq9nwr4JOFg7MLruaNVxhMhd7qUMbbKOLIcLW1WnyRFSIOWkI8vh4t+G1bId3FSnESLX9axXnEblPBj1+3FiH1tWL6dV51ax7+Y+JvlPwsXORXUcIXJf7fegdDNYM9DQPsvCSIGUUx5cgc3joGYfKNdCdRohlNBoNMx8zYdHSalMWndKdRyjufbwGnMOz+G1cq/RsGhD1XGEUEOjgc4LIDkeQizvKqoUSDlBp4Pg/pCvALQOUp1GCKWKuDowoVMV/jx6g79ORamOk206vY7AvYG42bkxovYI1XGEUMulGLSdCeG/wpkNqtMYlRRIOeHgUri6x3ATm52T6jRCKPdazaK0qFSIsatPcP9Rsuo42fJLxC8cvn2YKf5TyG+bX3UcIdTz7QHl2xqWs3l0T3Uao5ECydjunoetEw3TIEs1Vp1GCJOg0WiY9mo1UnV6xgefVB0nyy7HXmbe0Xm8VfEt6hauqzqOEKZBozG0z9KlwoZhqtMYjRRIxqRLg+B+4FzUsJCWECJdISd7pnSuyoYTt1gXflN1nExL1aUSsDcAT0dPBtccrDqOEKbFydPQRut0MJz8Q3Uao5ACyZj2zYcbR6DLYsPUfiHEEzr6FqG9T2HGrznJnYeJquNkyvJTyzl59yRBDYNwtJHzW4inVH0NqnQ1tNV6eFt1mmyTAslYbp+G7dPAbyAUr6c6jRAma0rnqlhrNYz54wR6vV51nAw59+Aci8IW0adyH6oXqq46jhCmq91c0FrDukGGtQDNmBRIxpCWAqs/Bvcy0HSs6jRCmDT3fLZMf9WHbWfu8PuR66rjvFSKLoWAPQEUdypO/xr9VccRwrTlKwAd58O5EAj7RXWabJECyRh2zYHbp6DrYrCxV51GCJPXsrInr9YsyuR1p7kZ81h1nBdadnwZ5x6cI6hREHZWdqrjCGH6KrYzzGwLGQ2xpv8h6HmkQMqum8dg9xxo/CkUqaE6jRBmY0LHKuSzs2bUH8dNdqjt1L1TfHX8Kz70+ZAqBaqojiOE+WgzA2zzw5oBZjvUJgVSdqQmwep+UKgyNJYF44TIDBcHG2a+7sPu83f5+UCk6jhPSUpLImBPAOXcyvFRtY9UxxHCvDi4Qucv4dJ2OPyt6jRZIgVSdmyfBvcvQtclYGWjOo0QZqdJ+YK8Va840zZGEHkvQXWcJywMW8iVuCsENQzCRs5vITKvbAuo9S78NR7uX1adJtOkQMqqawcN0/qbjgFPufQuRFaNbVcJ93y2jFgVjk5nGpfiw+6E8f2p7+lfvT/l3cqrjiOE+Wo1xXDjdvAnhjZcZkQKpKxIToDVfaFoLfAbpDqNEGYtv501c7r5cvDKfb7dq/5T5uPUxwTsDaBqgaq8U+Ud1XGEMG92Toa1ASP3wYHFqtNkihRIWbFtEsTdMLzpVtaq0whh9uqXLsC7/iWZvfksF+7EK83yxdEviHoUxdSGU7HWyvktRLaVbAj1+sG2yRB9TnWaDJMCKbMu74IDS6DFRPAopzqNEBZjZOuKFHV1YPiqcFLT1FyKP3jrID9H/MzgmoMp5VJKSQYhLFLzQHApBsF9IS1VdZoMkQIpM5Iewpr+UKIh1P1YdRohLIqDrRVz3vDlxPUYlu66lOvHf5TyiPF7x1PLsxY9K/XM9eMLYdFsHaHLEsPSOPu+UJ0mQ6RAyoy/AuDRPeiyELTyoxPC2GoWd+PjJmWYt/UcEbficvXYsw/N5kHSA6b4T0GrkfNbCKPzrgP+g2H7dIg6qTrNS8lvgYw6vxWOLIfWU8GtpOo0QlisIS3KUdojP8NXhpOcmjtDbXtu7OGP838wovYIvJ28c+WYQuRJTccYbk8J7gupyarTvJAUSBnx+AGsHQhlXjGs6SCEyDF21lbMfcOXc7cfsuDv8zl+vNikWCbsnUCDwg3oVr5bjh9PiDzN2s4wwelOBOyarTrNC0mBlBGbRkPyI+i0ADQa1WmEsHhVi7ow4JWyLNxxkePXY3L0WDMPziQhNYHJ/pPRyPktRM4rUt3Qnmv3XLhxVHWa55IC6WUi1sPx36DtTHApqjqNEHlG/2ZlqVTYiWErw0lMScuRY2yL3Ma6S+sYXXc0Xvm8cuQYQohnaDQcvKoa1hRMSVSd5pmkQHqRR/dg/RCo0A5831SdRog8xcZKy2dvVCfyXgKfbzH+2in3E+8zOXQyTYs1pVOZTkbfvxDiBaxsoOtSeHAZtgepTvNMUiA9j14PG4aCLg06zJOhNSEUKO/pxLBW5flq9yUOX7lvtP3q9Xqm7p9Kmj6NCX4TZGhNCBUKVYJm42DflxC5X3Wap0iB9Dwn/4DTa6D9XHDyVJ1GiDzrw0alqeHtyohV4SQkG2eBuZArIWy5uoWAegF4OHgYZZ9CiCzwGwjF6kBwP8O9viZECqRneRgFG0dAlVeh6quq0wiRp1lpNczp5ktUXCIzN53J9v6iE6KZun8qrUu2pk2pNkZIKITIMq2VYVZb3C3YOlF1midIgfRfej2sGwxaG8PVIyGEcqUL5mdUm4p8H3qVfRfuZnk/er2eSaGTsNZaM67eOCMmFEJkmUdZQ/uug1/BpZ2q06STAum/wn6BcyHQ8QtwdFedRgjx//o0KEn90u58+vtxHiamZGkfwReC2Xl9JxMbTMTN3s3ICYUQWVb3IyjZyNDOKzF3V9F/HimQ/i32OoSMBt+3oGI71WmEEP+i1WqY/bovMQnJBG2IyPTrb8XfYtahWXQq04lmxZvlQEIhRJZptdB5oWFh5r9M4+quFEj/o9cbKlc7J2gzXXUaIcQzeLs7EtChMr8dusb2M3cy/Dq9Xk/gvkAcbRwZVXdUDiYUQmSZWwloHQRHf4Bzf6lOIwVSusPfwKUd0OlLcHBVnUYI8Rxv1vGmSfmCjPrjODEJGevltPLsSvbf2s9kv8k42zrncEIhRJbV7ANlWxjaeyUYb2mPrJACCeD+JfgrEGq/B2Wbq04jhHgBjUbDzNd8SExJY+LaUy/d/lrcNeYemUu38t3wL+qfCwmFEFmm0RguVKQ+hk1qr/ZKgaTTQXB/yOcBLaeoTiOEyAAvF3smdqpCcNhNQk7eeu52abo0AvYG4G7vzvDaw3MxoRAiy5yLQNtZcGIlnF6rLIYUSAcWQ2QodFkEdvlVpxFCZFDXGkVpVdmTcatPci8+6Znb/BTxE0fvHGWK/xTy2eTL5YRCiCzz6Q4VO8D6ofAo60t7ZEfeLpCiz8HWSVC/H5RsqDqNECITNBoNQV2rodPrGbf6JHq9/onnL8VcYv7R+fSq1Is6XnUUpRRCZIlGAx0+B73O0BP1P+d3bsi7BVJaKgT3Bdfi0DxQdRohRBYUdLIjqGs1Qk5FsTb8ZvrjqbpUxu0ZR5H8RRhUc5DChEKILMtfyFAkRayDE7/n+uFNokBauHAhJUuWxN7ennr16nHw4MEXbr9q1SoqVqyIvb091apVY+PGjZk/6P5FcPMYdF0CNg5ZTC6EUK1dtcJ09C1C4JpT3I5LBOC7k99x+v5ppjacioO1nN9CmK0qXaDqa4b2X3HPv98wJygvkFasWMGwYcOYMGECR48exdfXl9atW3PnzrPXONm3bx89evTg/fff59ixY3Tp0oUuXbpw8uTJzB1492fgPwSK1c7+NyGEUGpypyrYWmsZ/cdxztw7w6LwRbxb5V18C/qqjiaEyK52c8DaDtbl7tVgjf6/A/e5rF69etSpU4cFCxYAoNPp8Pb2ZuDAgYwePfqp7bt3786jR49Yv359+mP169enevXqLFmy5KXHi4uLw8XFhXNza+H0/h+GH7oQwuztOR/NyNWhFCm3GjdHO75s8j22VraqYwkhjMDu0l8UWNsbJsbm2jGtc+1Iz5CcnMyRI0cYM2ZM+mNarZYWLVoQGhr6zNeEhoYybNiwJx5r3bo1wcHBz9w+KSmJpKR/ZrjExhp+uB00D7H6tW02vwMhhCmxLwx377tz/UQHGu9WvxKvEMJ4Jlv78WpcHE5OTmg0mhw/ntIC6e7du6SlpeHp6fnE456enpw5c+aZr4mKinrm9lFRUc/cfvr06UyaNOmpx88NO5fF1EII07dXdQAhhJG9C7w7x4U7d+5QsGDBHD+e0gIpN4wZM+aJK046nY779+9ToECBXKlAxfPFxcXh7e3NtWvXcHaW9g8qyXthOuS9MC3yfpiO/70Xtra5M3SutEDy8PDAysqK27dvP/H47du38fLyeuZrvLy8MrW9nZ0ddnZP3mfk6uqa9dDC6JydneUXj4mQ98J0yHthWuT9MB25dXFD6Sw2W1tbatWqxbZt29If0+l0bNu2jQYNGjzzNQ0aNHhie4AtW7Y8d3shhBBCiMxSPsQ2bNgw+vTpQ+3atalbty7z5s3j0aNHvPvuuwD07t2bokWLMn36dAAGDx5MkyZNmDt3Lu3bt+e3337j8OHDfPXVVyq/DSGEEEJYEOUFUvfu3YmOjiYwMJCoqCiqV69OSEhI+o3YkZGRaLX/XOjy8/Pjl19+ISAggLFjx1KuXDmCg4OpWrWqqm9BZJGdnR0TJkx4aghU5D55L0yHvBemRd4P05Hb74XydZCEEEIIIUyN8pW0hRBCCCFMjRRIQgghhBD/IQWSEEIIIcR/SIEkhBBCCPEfUiCJLJs+fTp16tTBycmJQoUK0aVLF86ePfvENomJifTv358CBQqQP39+XnvttacW+oyMjKR9+/Y4OjpSqFAhPv30U1JTU5/YZseOHdSsWRM7OzvKli3L8uXLc/rbMzuLFy/Gx8cnfUG7Bg0asGnTpvTn5b1QZ8aMGWg0GoYMGZL+mLwfuWPixIloNJonvipWrJj+vLwPue/GjRv06tWLAgUK4ODgQLVq1Th8+HD683q9nsDAQAoXLoyDgwMtWrTg/PnzT+zj/v379OzZE2dnZ1xdXXn//feJj49/Ypvjx4/TqFEj7O3t8fb2ZtasWZkLqhcii1q3bq3/7rvv9CdPntSHhYXp27Vrpy9evLg+Pj4+fZu+ffvqvb299du2bdMfPnxYX79+fb2fn1/686mpqfqqVavqW7RooT927Jh+48aNeg8PD/2YMWPSt7l06ZLe0dFRP2zYMP3p06f1X375pd7KykofEhKSq9+vqVu7dq1+w4YN+nPnzunPnj2rHzt2rN7GxkZ/8uRJvV4v74UqBw8e1JcsWVLv4+OjHzx4cPrj8n7kjgkTJuirVKmiv3XrVvpXdHR0+vPyPuSu+/fv60uUKKF/55139AcOHNBfunRJv3nzZv2FCxfSt5kxY4bexcVFHxwcrA8PD9d36tRJX6pUKf3jx4/Tt2nTpo3e19dXv3//fv3u3bv1ZcuW1ffo0SP9+djYWL2np6e+Z8+e+pMnT+p//fVXvYODg37p0qUZzioFkjCaO3fu6AH9zp079Xq9Xh8TE6O3sbHRr1q1Kn2biIgIPaAPDQ3V6/V6/caNG/VarVYfFRWVvs3ixYv1zs7O+qSkJL1er9ePHDlSX6VKlSeO1b17d33r1q1z+lsye25ubvqvv/5a3gtFHj58qC9Xrpx+y5Yt+iZNmqQXSPJ+5J4JEybofX19n/mcvA+5b9SoUfqGDRs+93mdTqf38vLSz549O/2xmJgYvZ2dnf7XX3/V6/V6/enTp/WA/tChQ+nbbNq0Sa/RaPQ3btzQ6/V6/aJFi/Rubm7p79H/jl2hQoUMZ5UhNmE0sbGxALi7uwNw5MgRUlJSaNGiRfo2FStWpHjx4oSGhgIQGhpKtWrV0hcGBWjdujVxcXGcOnUqfZt/7+N/2/xvH+JpaWlp/Pbbbzx69IgGDRrIe6FI//79ad++/VM/M3k/ctf58+cpUqQIpUuXpmfPnkRGRgLyPqiwdu1aateuTbdu3ShUqBA1atRg2bJl6c9fvnyZqKioJ36eLi4u1KtX74n3xNXVldq1a6dv06JFC7RaLQcOHEjfpnHjxk80tm3dujVnz57lwYMHGcoqBZIwCp1Ox5AhQ/D3909f1TwqKgpbW9unmgN7enoSFRWVvs2/f/H87/n/PfeibeLi4nj8+HFOfDtm68SJE+TPnx87Ozv69u3L6tWrqVy5srwXCvz2228cPXo0vU3Sv8n7kXvq1avH8uXLCQkJYfHixVy+fJlGjRrx8OFDeR8UuHTpEosXL6ZcuXJs3ryZfv36MWjQIL7//nvgn5/ps36e//55FypU6Innra2tcXd3z9T79jLKW40Iy9C/f39OnjzJnj17VEfJ0ypUqEBYWBixsbH8/vvv9OnTh507d6qOledcu3aNwYMHs2XLFuzt7VXHydPatm2b/t8+Pj7Uq1ePEiVKsHLlShwcHBQmy5t0Oh21a9dm2rRpANSoUYOTJ0+yZMkS+vTpozjdk+QKksi2AQMGsH79erZv306xYsXSH/fy8iI5OZmYmJgntr99+zZeXl7p2/x3xsj//v/LtnF2dpZfcP9ha2tL2bJlqVWrFtOnT8fX15cvvvhC3otcduTIkf9r7/5jqqr/P4A/LyKXe7lwLwO6F9F7wXkRkJUKW9xZXo3UwaIym0yZ8SNcZixYDLGMaZGNas2py62auxRYtmYWMFEZvzJEQuGizssFr5euThYBEt2RBNzX54++nHUvJCKfuH2+vB7b3Tjn/Trv8z7vNxdeO/f9vgc9PT1YuXIlPD094enpifr6ehw6dAienp5QKpU8Hm6iUCgQHh6O69ev8/vCDYKDgxEVFeW0LzIyUvjYc7xPJ+vPv/Z3T0+PU/no6Cj6+/unNW5T4QSJPTAiQlZWFk6ePImamhqEhYU5lcfExGD+/Pmorq4W9pnNZthsNuh0OgCATqfDlStXnH7Zq6qq4OfnJ7yJdDqdUx3jMeN1sL/ncDgwPDzMYzHL4uPjceXKFRiNRuEVGxuLlJQU4WceD/ew2+2wWCwIDg7m94UbrFq1asLXwXR0dECj0QAAwsLCoFKpnPpzcHAQTU1NTmMyMDCAS5cuCTE1NTVwOBx49NFHhZjvv/8eIyMjQkxVVRWWLl0Kf3//+2vsfU/nZszFyy+/THK5nOrq6pyW0A4NDQkxO3bsILVaTTU1NXTx4kXS6XSk0+mE8vEltOvXryej0UinT5+moKCgSZfQ5uXlkclkoo8++oiX0E5i9+7dVF9fT1arlS5fvky7d+8mkUhEZ8+eJSIeC3f76yo2Ih6P2ZKbm0t1dXVktVqpoaGBnnzySQoMDKSenh4i4nGYbT/++CN5enrS/v37qbOzk44dO0ZSqZRKS0uFmKKiIlIoFPTdd9/R5cuX6Zlnnpl0mf+KFSuoqamJfvjhB9JqtU7L/AcGBkipVNK2bdvo6tWrdPz4cZJKpbzMn80OAJO+DAaDEPP777/Tzp07yd/fn6RSKW3cuJG6u7ud6unq6qKEhASSSCQUGBhIubm5NDIy4hRTW1tLy5cvJy8vL1q8eLHTOdifMjIySKPRkJeXFwUFBVF8fLyQHBHxWLiba4LE4zE7kpOTKTg4mLy8vCgkJISSk5OdvnOHx2H2lZeXU3R0NInFYoqIiKBPPvnEqdzhcFBBQQEplUoSi8UUHx9PZrPZKaavr4+2bNlCMpmM/Pz8KD09nX777TenmLa2NnrsscdILBZTSEgIFRUVTaudIiKiad4hY4wxxhj7f43nIDHGGGOMueAEiTHGGGPMBSdIjDHGGGMuOEFijDHGGHPBCRJjjDHGmAtOkBhjjDHGXHCCxBhjjDHmghMkxhhjjDEXnCAxNoesWbMGOTk57m7GnFdcXAyFQuHuZjDG7oETJMbYfaurq4NIJJrw9HNOvKYnOTkZHR0dwva+ffuwfPly9zWIMTaBp7sbwBhj4/744w94eXm5uxn/OIlEAolE4u5mMMbuge8gMTbHjI6OIisrC3K5HIGBgSgoKMD4IxlLSkoQGxsLX19fqFQqbN26FT09PQCArq4urF27FgDg7+8PkUiEtLQ0pKWlob6+HgcPHoRIJIJIJEJXVxcA4OrVq0hISIBMJoNSqcS2bdvQ29srtGXNmjXIyspCTk4OAgMDsWHDBmRkZOCpp55yavPIyAgeeughHD16dMrrczgceP/997FkyRKIxWKo1Wrs379fKM/Pz0d4eDikUikWL16MgoICjIyMCOXjd3M+/vhjLFq0CFKpFJs3b8avv/4qxDQ3N2PdunUIDAyEXC6HXq9HS0uLUzsGBgbw0ksvQalUwtvbG9HR0aioqADg/BFbcXEx3nrrLbS1tQn9V1xcPON+YIzN0AM8iJcx9j9Kr9eTTCaj7Oxsam9vp9LSUpJKpcLTtI8ePUqnTp0ii8VCjY2NpNPpKCEhgYiIRkdH6cSJEwSAzGYzdXd308DAAA0MDJBOp6Pt27dTd3c3dXd30+joKN25c4eCgoLo9ddfJ5PJRC0tLbRu3Tpau3bthPbk5eVRe3s7tbe3U0NDA82bN49u374txH3zzTfk4+Mz4Wndk9m1axf5+/tTcXExXb9+nc6dO0effvqpUF5YWEgNDQ1ktVqprKyMlEolvffee0L53r17ycfHh5544glqbW2l+vp6WrJkCW3dulWIqa6uppKSEjKZTHTt2jV68cUXSalU0uDgIBERjY2NUVxcHC1btozOnj1LFouFysvL6dSpU0REZDAYSC6XExHR0NAQ5ebm0rJly4T+GxoamnE/MMZmhhMkxuYQvV5PkZGR5HA4hH35+fkUGRk5aXxzczMBEP4h19bWEgC6c+fOhHqzs7Od9hUWFtL69eud9t28eVNIsMaPW7FixYTzRkVFOSUtSUlJlJaWNuX1DQ4OklgsdkqIpvLBBx9QTEyMsL13716aN28e3bp1S9hXWVlJHh4e1N3dPWkdY2Nj5OvrS+Xl5UREdObMGfLw8BCu09VfE6Txcz7yyCMT4h60HxhjM8cfsTE2x8TFxUEkEgnbOp0OnZ2dGBsbw6VLl5CUlAS1Wg1fX1/o9XoAgM1mm/Z52traUFtbC5lMJrwiIiIAABaLRYiLiYmZcGxmZiYMBgMA4Oeff0ZlZSUyMjKmPKfJZMLw8DDi4+P/Nuarr77CqlWroFKpIJPJ8Oabb064PrVajZCQEGFbp9PB4XDAbDYLbdq+fTu0Wi3kcjn8/Pxgt9uFeoxGIxYuXIjw8PAp23wvD9oPjLGZ4wSJMQYAuHv3LjZs2AA/Pz8cO3YMzc3NOHnyJIA/J09Pl91uR1JSEoxGo9Ors7MTq1evFuJ8fHwmHPvCCy/gxo0baGxsRGlpKcLCwvD4449Pec6pJj43NjYiJSUFiYmJqKioQGtrK/bs2TPt60tNTYXRaMTBgwdx/vx5GI1GBAQECPX8tyZgP2g/MMZmjlexMTbHNDU1OW1fuHABWq0W7e3t6OvrQ1FRERYtWgQAuHjxolPs+AqzsbGxCftd961cuRInTpxAaGgoPD2n96cmICAAzz77LAwGAxobG5Genn5fx2m1WkgkElRXVyMzM3NC+fnz56HRaLBnzx5h308//TQhzmaz4fbt21iwYAGAP/vIw8MDS5cuBQA0NDTgyJEjSExMBADcvHnTafL5ww8/jFu3bqGjo+O+7iJN1n/Ag/cDY2zm+A4SY3OMzWbDa6+9BrPZjC+//BKHDx9GdnY21Go1vLy8cPjwYdy4cQNlZWUoLCx0Olaj0UAkEqGiogK//PIL7HY7ACA0NBRNTU3o6upCb28vHA4HXnnlFfT392PLli1obm6GxWLBmTNnkJ6ePmky4CozMxOfffYZTCYTUlNT7+vavL29kZ+fj127duHzzz+HxWLBhQsXhFVfWq0WNpsNx48fh8ViwaFDh4S7ZK71pKamoq2tDefOncOrr76KzZs3Q6VSCfWUlJTAZDKhqakJKSkpTneN9Ho9Vq9ejU2bNqGqqgpWqxWVlZU4ffr0pO0ODQ2F1WqF0WhEb28vhoeHZ9QPjLH/AndPgmKMzR69Xk87d+6kHTt2kJ+fH/n7+9Mbb7whTNr+4osvKDQ0lMRiMel0OiorKyMA1NraKtTx9ttvk0qlIpFIRKmpqUREZDabKS4ujiQSCQEgq9VKREQdHR20ceNGUigUJJFIKCIignJycoTzTTa5e5zD4SCNRkOJiYnTusaxsTF65513SKPR0Pz580mtVtO7774rlOfl5VFAQADJZDJKTk6mAwcOTDph+siRI7RgwQLy9vam559/nvr7+4WYlpYWio2NJW9vb9JqtfT111+TRqOhAwcOCDF9fX2Unp5OAQEB5O3tTdHR0VRRUUFEEydp3717lzZt2kQKhYIAkMFgmHE/MMZmRkT0f1+Awhhj/yJ2ux0hISEwGAx47rnnZu28+/btw7fffguj0Thr57wXd/UDY3Mdz0FijP2rOBwO9Pb24sMPP4RCocDTTz/t7ia5BfcDY+7FCRJj7F/FZrMhLCwMCxcuRHFxsdMEb5vNhqioqL899tq1a1Cr1bPRzH/cvfqBMfbP44/YGGP/M0ZHR4XHmEzmQVbMMcbYZDhBYowxxhhzwcv8GWOMMcZccILEGGOMMeaCEyTGGGOMMRecIDHGGGOMueAEiTHGGGPMBSdIjDHGGGMuOEFijDHGGHPxH7EV4ojMfR96AAAAAElFTkSuQmCC",
+      "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": [
+    "data = pd.read_csv(\"..//static//csv//ndtv_data_final.csv\")\n",
+    "\n",
+    "# Инициализация нечетких переменных\n",
+    "battery_capacity = ctrl.Antecedent(data[\"Battery capacity (mAh)\"].sort_values().unique(), \"battery_capacity\")\n",
+    "ram = ctrl.Antecedent(data[\"RAM (MB)\"].sort_values().unique(), \"ram\")\n",
+    "price = ctrl.Consequent(np.arange(0, 100001, 1000), \"price\")\n",
+    "\n",
+    "battery_capacity.automf(3, variable_type=\"quant\")\n",
+    "battery_capacity.view()\n",
+    "ram.automf(3, variable_type=\"quant\")\n",
+    "ram.view()\n",
+    "price.automf(5, variable_type=\"quant\")\n",
+    "price.view()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Нечеткие правила**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 128,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "rule1 = ctrl.Rule(\n",
+    "    battery_capacity[\"low\"] & ram[\"low\"],\n",
+    "    price[\"low\"],\n",
+    ")\n",
+    "rule2 = ctrl.Rule(\n",
+    "    battery_capacity[\"average\"] & ram[\"low\"],\n",
+    "    price[\"low\"],\n",
+    ")\n",
+    "rule3 = ctrl.Rule(\n",
+    "    battery_capacity[\"high\"] & ram[\"low\"],\n",
+    "    price[\"average\"],\n",
+    ")\n",
+    "\n",
+    "rule4 = ctrl.Rule(\n",
+    "    battery_capacity[\"low\"] & ram[\"average\"],\n",
+    "    price[\"low\"],\n",
+    ")\n",
+    "rule5 = ctrl.Rule(\n",
+    "    battery_capacity[\"average\"] & ram[\"average\"],\n",
+    "    price[\"average\"],\n",
+    ")\n",
+    "rule6 = ctrl.Rule(\n",
+    "    battery_capacity[\"high\"] & ram[\"average\"],\n",
+    "    price[\"high\"],\n",
+    ")\n",
+    "\n",
+    "rule7 = ctrl.Rule(\n",
+    "    battery_capacity[\"low\"] & ram[\"high\"],\n",
+    "    price[\"average\"],\n",
+    ")\n",
+    "rule8 = ctrl.Rule(\n",
+    "    battery_capacity[\"average\"] & ram[\"high\"],\n",
+    "    price[\"high\"],\n",
+    ")\n",
+    "rule9 = ctrl.Rule(\n",
+    "    battery_capacity[\"high\"] & ram[\"high\"],\n",
+    "    price[\"high\"],\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Создание нечеткой системы**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 129,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[IF battery_capacity[low] AND ram[low] THEN price[low]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax,\n",
+       " IF battery_capacity[average] AND ram[low] THEN price[low]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax,\n",
+       " IF battery_capacity[high] AND ram[low] THEN price[average]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax,\n",
+       " IF battery_capacity[low] AND ram[average] THEN price[low]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax,\n",
+       " IF battery_capacity[average] AND ram[average] THEN price[average]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax,\n",
+       " IF battery_capacity[high] AND ram[average] THEN price[high]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax,\n",
+       " IF battery_capacity[low] AND ram[high] THEN price[average]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax,\n",
+       " IF battery_capacity[average] AND ram[high] THEN price[high]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax,\n",
+       " IF battery_capacity[high] AND ram[high] THEN price[high]\n",
+       " \tAND aggregation function : fmin\n",
+       " \tOR aggregation function  : fmax]"
+      ]
+     },
+     "execution_count": 129,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "fuzzy_rules = [\n",
+    "    rule1,\n",
+    "    rule2,\n",
+    "    rule3,\n",
+    "    rule4,\n",
+    "    rule5,\n",
+    "    rule6,\n",
+    "    rule7,\n",
+    "    rule8,\n",
+    "    rule9,\n",
+    "]\n",
+    "\n",
+    "price_cntrl = ctrl.ControlSystem(fuzzy_rules)\n",
+    "\n",
+    "sim = ctrl.ControlSystemSimulation(price_cntrl)\n",
+    "\n",
+    "fuzzy_rules"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Пример использования полученной нечеткой системы**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 130,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "=============\n",
+      " Antecedents \n",
+      "=============\n",
+      "Antecedent: battery_capacity        = 3110\n",
+      "  - low                             : 0.15831663326653306\n",
+      "  - average                         : 0.8416833667334669\n",
+      "  - high                            : 0.0\n",
+      "Antecedent: ram                     = 4000\n",
+      "  - low                             : 0.34048257372654156\n",
+      "  - average                         : 0.6595174262734584\n",
+      "  - high                            : 0.0\n",
+      "\n",
+      "=======\n",
+      " Rules \n",
+      "=======\n",
+      "RULE #0:\n",
+      "  IF battery_capacity[low] AND ram[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[low]                                  : 0.15831663326653306\n",
+      "  - ram[low]                                               : 0.34048257372654156\n",
+      "                        battery_capacity[low] AND ram[low] = 0.15831663326653306\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.15831663326653306\n",
+      "\n",
+      "RULE #1:\n",
+      "  IF battery_capacity[average] AND ram[low] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[average]                              : 0.8416833667334669\n",
+      "  - ram[low]                                               : 0.34048257372654156\n",
+      "                    battery_capacity[average] AND ram[low] = 0.34048257372654156\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.34048257372654156\n",
+      "\n",
+      "RULE #2:\n",
+      "  IF battery_capacity[high] AND ram[low] THEN price[average]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[high]                                 : 0.0\n",
+      "  - ram[low]                                               : 0.34048257372654156\n",
+      "                       battery_capacity[high] AND ram[low] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                            price[average] : 0.0\n",
+      "\n",
+      "RULE #3:\n",
+      "  IF battery_capacity[low] AND ram[average] THEN price[low]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[low]                                  : 0.15831663326653306\n",
+      "  - ram[average]                                           : 0.6595174262734584\n",
+      "                    battery_capacity[low] AND ram[average] = 0.15831663326653306\n",
+      "  Activation (THEN-clause):\n",
+      "                                                price[low] : 0.15831663326653306\n",
+      "\n",
+      "RULE #4:\n",
+      "  IF battery_capacity[average] AND ram[average] THEN price[average]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[average]                              : 0.8416833667334669\n",
+      "  - ram[average]                                           : 0.6595174262734584\n",
+      "                battery_capacity[average] AND ram[average] = 0.6595174262734584\n",
+      "  Activation (THEN-clause):\n",
+      "                                            price[average] : 0.6595174262734584\n",
+      "\n",
+      "RULE #5:\n",
+      "  IF battery_capacity[high] AND ram[average] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[high]                                 : 0.0\n",
+      "  - ram[average]                                           : 0.6595174262734584\n",
+      "                   battery_capacity[high] AND ram[average] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #6:\n",
+      "  IF battery_capacity[low] AND ram[high] THEN price[average]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[low]                                  : 0.15831663326653306\n",
+      "  - ram[high]                                              : 0.0\n",
+      "                       battery_capacity[low] AND ram[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                            price[average] : 0.0\n",
+      "\n",
+      "RULE #7:\n",
+      "  IF battery_capacity[average] AND ram[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[average]                              : 0.8416833667334669\n",
+      "  - ram[high]                                              : 0.0\n",
+      "                   battery_capacity[average] AND ram[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "RULE #8:\n",
+      "  IF battery_capacity[high] AND ram[high] THEN price[high]\n",
+      "\tAND aggregation function : fmin\n",
+      "\tOR aggregation function  : fmax\n",
+      "\n",
+      "  Aggregation (IF-clause):\n",
+      "  - battery_capacity[high]                                 : 0.0\n",
+      "  - ram[high]                                              : 0.0\n",
+      "                      battery_capacity[high] AND ram[high] = 0.0\n",
+      "  Activation (THEN-clause):\n",
+      "                                               price[high] : 0.0\n",
+      "\n",
+      "\n",
+      "==============================\n",
+      " Intermediaries and Conquests \n",
+      "==============================\n",
+      "Consequent: price                    = 40755.45920618248\n",
+      "  lower:\n",
+      "    Accumulate using accumulation_max : None\n",
+      "  low:\n",
+      "    Accumulate using accumulation_max : 0.34048257372654156\n",
+      "  average:\n",
+      "    Accumulate using accumulation_max : 0.6595174262734584\n",
+      "  high:\n",
+      "    Accumulate using accumulation_max : 0.0\n",
+      "  higher:\n",
+      "    Accumulate using accumulation_max : None\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(40755.45920618248)"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "example_row = data.iloc[3]  # Используем строку в качестве примера\n",
+    "\n",
+    "sim.input[\"battery_capacity\"] = example_row[\"Battery capacity (mAh)\"]\n",
+    "sim.input[\"ram\"] = example_row[\"RAM (MB)\"]\n",
+    "\n",
+    "sim.compute()\n",
+    "\n",
+    "sim.print_state()\n",
+    "display(sim.output[\"price\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Функция для автоматизации вычисления целевой переменной Y на основе вектора признаков X**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 131,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Index(['Unnamed: 0', 'Name', 'Brand', 'Model', 'Battery capacity (mAh)',\n",
+      "       'Screen size (inches)', 'Touchscreen', 'Resolution x', 'Resolution y',\n",
+      "       'Processor', 'RAM (MB)', 'Internal storage (GB)', 'Rear camera',\n",
+      "       'Front camera', 'Operating system', 'Wi-Fi', 'Bluetooth', 'GPS',\n",
+      "       'Number of SIMs', '3G', '4G/ LTE', 'Price'],\n",
+      "      dtype='object')\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(data_train.columns)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 132,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def fuzzy_pred(row):\n",
+    "    sim.input[\"battery_capacity\"] = row[\"Battery capacity (mAh)\"]\n",
+    "    sim.input[\"ram\"] = row[\"RAM (MB)\"]\n",
+    "    sim.compute()\n",
+    "    return sim.output[\"price\"]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Тестирование нечеткой системы на обучающей выборке**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 133,
+   "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>Unnamed: 0</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Brand</th>\n",
+       "      <th>Model</th>\n",
+       "      <th>Battery capacity (mAh)</th>\n",
+       "      <th>Screen size (inches)</th>\n",
+       "      <th>Touchscreen</th>\n",
+       "      <th>Resolution x</th>\n",
+       "      <th>Resolution y</th>\n",
+       "      <th>Processor</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Front camera</th>\n",
+       "      <th>Operating system</th>\n",
+       "      <th>Wi-Fi</th>\n",
+       "      <th>Bluetooth</th>\n",
+       "      <th>GPS</th>\n",
+       "      <th>Number of SIMs</th>\n",
+       "      <th>3G</th>\n",
+       "      <th>4G/ LTE</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Predicted Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>OnePlus 7T Pro McLaren Edition</td>\n",
+       "      <td>OnePlus</td>\n",
+       "      <td>7T Pro McLaren Edition</td>\n",
+       "      <td>4085</td>\n",
+       "      <td>6.67</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1440</td>\n",
+       "      <td>3120</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>58998</td>\n",
+       "      <td>75000.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Realme X2 Pro</td>\n",
+       "      <td>Realme</td>\n",
+       "      <td>X2 Pro</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>27999</td>\n",
+       "      <td>55792.501783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>Apple</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>3969</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1242</td>\n",
+       "      <td>2688</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>iOS</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>106900</td>\n",
+       "      <td>46614.283392</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>iPhone 11</td>\n",
+       "      <td>Apple</td>\n",
+       "      <td>iPhone 11</td>\n",
+       "      <td>3110</td>\n",
+       "      <td>6.10</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>828</td>\n",
+       "      <td>1792</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>iOS</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>62900</td>\n",
+       "      <td>40755.459206</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>LG G8X ThinQ</td>\n",
+       "      <td>LG</td>\n",
+       "      <td>G8X ThinQ</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.40</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1</td>\n",
+       "      <td>No</td>\n",
+       "      <td>No</td>\n",
+       "      <td>49990</td>\n",
+       "      <td>55792.501783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>5</td>\n",
+       "      <td>OnePlus 7T</td>\n",
+       "      <td>OnePlus</td>\n",
+       "      <td>7T</td>\n",
+       "      <td>3800</td>\n",
+       "      <td>6.55</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>No</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>34930</td>\n",
+       "      <td>59015.272109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>6</td>\n",
+       "      <td>OnePlus 7T Pro</td>\n",
+       "      <td>OnePlus</td>\n",
+       "      <td>7T Pro</td>\n",
+       "      <td>4085</td>\n",
+       "      <td>6.67</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1440</td>\n",
+       "      <td>3120</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>52990</td>\n",
+       "      <td>59015.272109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>7</td>\n",
+       "      <td>Samsung Galaxy Note 10+</td>\n",
+       "      <td>Samsung</td>\n",
+       "      <td>Galaxy Note 10+</td>\n",
+       "      <td>4300</td>\n",
+       "      <td>6.80</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1440</td>\n",
+       "      <td>3040</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>79699</td>\n",
+       "      <td>75000.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>8</td>\n",
+       "      <td>Asus ROG Phone 2</td>\n",
+       "      <td>Asus</td>\n",
+       "      <td>ROG Phone 2</td>\n",
+       "      <td>6000</td>\n",
+       "      <td>6.59</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>37999</td>\n",
+       "      <td>75000.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>9</td>\n",
+       "      <td>Xiaomi Redmi K20 Pro</td>\n",
+       "      <td>Xiaomi</td>\n",
+       "      <td>Redmi K20 Pro</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.39</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>No</td>\n",
+       "      <td>No</td>\n",
+       "      <td>23190</td>\n",
+       "      <td>55792.501783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>10</td>\n",
+       "      <td>Oppo K3</td>\n",
+       "      <td>Oppo</td>\n",
+       "      <td>K3</td>\n",
+       "      <td>3765</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>23990</td>\n",
+       "      <td>53251.486942</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>11</td>\n",
+       "      <td>Realme X</td>\n",
+       "      <td>Realme</td>\n",
+       "      <td>X</td>\n",
+       "      <td>3765</td>\n",
+       "      <td>6.53</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>14999</td>\n",
+       "      <td>44322.761836</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>12</td>\n",
+       "      <td>Xiaomi Redmi K20</td>\n",
+       "      <td>Xiaomi</td>\n",
+       "      <td>Redmi K20</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.39</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>19282</td>\n",
+       "      <td>55792.501783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>13</td>\n",
+       "      <td>OnePlus 7 Pro</td>\n",
+       "      <td>OnePlus</td>\n",
+       "      <td>7 Pro</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.67</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1440</td>\n",
+       "      <td>3120</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>39995</td>\n",
+       "      <td>55792.501783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>14</td>\n",
+       "      <td>Oppo Reno 10x Zoom</td>\n",
+       "      <td>Oppo</td>\n",
+       "      <td>Reno 10x Zoom</td>\n",
+       "      <td>4065</td>\n",
+       "      <td>6.60</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>36990</td>\n",
+       "      <td>56431.899431</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>15 rows × 23 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    Unnamed: 0                            Name    Brand  \\\n",
+       "0            0  OnePlus 7T Pro McLaren Edition  OnePlus   \n",
+       "1            1                   Realme X2 Pro   Realme   \n",
+       "2            2               iPhone 11 Pro Max    Apple   \n",
+       "3            3                       iPhone 11    Apple   \n",
+       "4            4                    LG G8X ThinQ       LG   \n",
+       "5            5                      OnePlus 7T  OnePlus   \n",
+       "6            6                  OnePlus 7T Pro  OnePlus   \n",
+       "7            7         Samsung Galaxy Note 10+  Samsung   \n",
+       "8            8                Asus ROG Phone 2     Asus   \n",
+       "9            9            Xiaomi Redmi K20 Pro   Xiaomi   \n",
+       "10          10                         Oppo K3     Oppo   \n",
+       "11          11                        Realme X   Realme   \n",
+       "12          12                Xiaomi Redmi K20   Xiaomi   \n",
+       "13          13                   OnePlus 7 Pro  OnePlus   \n",
+       "14          14              Oppo Reno 10x Zoom     Oppo   \n",
+       "\n",
+       "                     Model  Battery capacity (mAh)  Screen size (inches)  \\\n",
+       "0   7T Pro McLaren Edition                    4085                  6.67   \n",
+       "1                   X2 Pro                    4000                  6.50   \n",
+       "2        iPhone 11 Pro Max                    3969                  6.50   \n",
+       "3                iPhone 11                    3110                  6.10   \n",
+       "4                G8X ThinQ                    4000                  6.40   \n",
+       "5                       7T                    3800                  6.55   \n",
+       "6                   7T Pro                    4085                  6.67   \n",
+       "7          Galaxy Note 10+                    4300                  6.80   \n",
+       "8              ROG Phone 2                    6000                  6.59   \n",
+       "9            Redmi K20 Pro                    4000                  6.39   \n",
+       "10                      K3                    3765                  6.50   \n",
+       "11                       X                    3765                  6.53   \n",
+       "12               Redmi K20                    4000                  6.39   \n",
+       "13                   7 Pro                    4000                  6.67   \n",
+       "14           Reno 10x Zoom                    4065                  6.60   \n",
+       "\n",
+       "   Touchscreen  Resolution x  Resolution y  Processor  ...  Front camera  \\\n",
+       "0          Yes          1440          3120          8  ...          16.0   \n",
+       "1          Yes          1080          2400          8  ...          16.0   \n",
+       "2          Yes          1242          2688          6  ...          12.0   \n",
+       "3          Yes           828          1792          6  ...          12.0   \n",
+       "4          Yes          1080          2340          8  ...          32.0   \n",
+       "5          Yes          1080          2400          8  ...          16.0   \n",
+       "6          Yes          1440          3120          8  ...          16.0   \n",
+       "7          Yes          1440          3040          8  ...          10.0   \n",
+       "8          Yes          1080          2340          8  ...          24.0   \n",
+       "9          Yes          1080          2340          8  ...          20.0   \n",
+       "10         Yes          1080          2340          8  ...          16.0   \n",
+       "11         Yes          1080          2340          8  ...          16.0   \n",
+       "12         Yes          1080          2340          8  ...          20.0   \n",
+       "13         Yes          1440          3120          8  ...          16.0   \n",
+       "14         Yes          1080          2340          8  ...          16.0   \n",
+       "\n",
+       "    Operating system  Wi-Fi  Bluetooth  GPS Number of SIMs   3G 4G/ LTE  \\\n",
+       "0            Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "1            Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "2                iOS    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "3                iOS    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "4            Android    Yes        Yes  Yes              1   No      No   \n",
+       "5            Android    Yes        Yes   No              2  Yes     Yes   \n",
+       "6            Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "7            Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "8            Android    Yes        Yes  Yes              1  Yes     Yes   \n",
+       "9            Android    Yes        Yes  Yes              2   No      No   \n",
+       "10           Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "11           Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "12           Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "13           Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "14           Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "\n",
+       "     Price Predicted Price  \n",
+       "0    58998    75000.000000  \n",
+       "1    27999    55792.501783  \n",
+       "2   106900    46614.283392  \n",
+       "3    62900    40755.459206  \n",
+       "4    49990    55792.501783  \n",
+       "5    34930    59015.272109  \n",
+       "6    52990    59015.272109  \n",
+       "7    79699    75000.000000  \n",
+       "8    37999    75000.000000  \n",
+       "9    23190    55792.501783  \n",
+       "10   23990    53251.486942  \n",
+       "11   14999    44322.761836  \n",
+       "12   19282    55792.501783  \n",
+       "13   39995    55792.501783  \n",
+       "14   36990    56431.899431  \n",
+       "\n",
+       "[15 rows x 23 columns]"
+      ]
+     },
+     "execution_count": 133,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result_train = data_train.copy()\n",
+    "result_train[\"Predicted Price\"] = result_train.apply(fuzzy_pred, axis=1)\n",
+    "\n",
+    "result_train.head(15)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "**Тестирование нечеткой системы на тестовой выборке**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 135,
+   "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>Unnamed: 0</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Brand</th>\n",
+       "      <th>Model</th>\n",
+       "      <th>Battery capacity (mAh)</th>\n",
+       "      <th>Screen size (inches)</th>\n",
+       "      <th>Touchscreen</th>\n",
+       "      <th>Resolution x</th>\n",
+       "      <th>Resolution y</th>\n",
+       "      <th>Processor</th>\n",
+       "      <th>...</th>\n",
+       "      <th>Front camera</th>\n",
+       "      <th>Operating system</th>\n",
+       "      <th>Wi-Fi</th>\n",
+       "      <th>Bluetooth</th>\n",
+       "      <th>GPS</th>\n",
+       "      <th>Number of SIMs</th>\n",
+       "      <th>3G</th>\n",
+       "      <th>4G/ LTE</th>\n",
+       "      <th>Price</th>\n",
+       "      <th>Predicted Price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>OnePlus 7T Pro McLaren Edition</td>\n",
+       "      <td>OnePlus</td>\n",
+       "      <td>7T Pro McLaren Edition</td>\n",
+       "      <td>4085</td>\n",
+       "      <td>6.67</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1440</td>\n",
+       "      <td>3120</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>58998</td>\n",
+       "      <td>75000.000000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Realme X2 Pro</td>\n",
+       "      <td>Realme</td>\n",
+       "      <td>X2 Pro</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2400</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>27999</td>\n",
+       "      <td>55792.501783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>Apple</td>\n",
+       "      <td>iPhone 11 Pro Max</td>\n",
+       "      <td>3969</td>\n",
+       "      <td>6.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1242</td>\n",
+       "      <td>2688</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>iOS</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>106900</td>\n",
+       "      <td>46614.283392</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>iPhone 11</td>\n",
+       "      <td>Apple</td>\n",
+       "      <td>iPhone 11</td>\n",
+       "      <td>3110</td>\n",
+       "      <td>6.10</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>828</td>\n",
+       "      <td>1792</td>\n",
+       "      <td>6</td>\n",
+       "      <td>...</td>\n",
+       "      <td>12.0</td>\n",
+       "      <td>iOS</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>62900</td>\n",
+       "      <td>40755.459206</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>LG G8X ThinQ</td>\n",
+       "      <td>LG</td>\n",
+       "      <td>G8X ThinQ</td>\n",
+       "      <td>4000</td>\n",
+       "      <td>6.40</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1080</td>\n",
+       "      <td>2340</td>\n",
+       "      <td>8</td>\n",
+       "      <td>...</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>1</td>\n",
+       "      <td>No</td>\n",
+       "      <td>No</td>\n",
+       "      <td>49990</td>\n",
+       "      <td>55792.501783</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1354</th>\n",
+       "      <td>1354</td>\n",
+       "      <td>Intex Aqua A2</td>\n",
+       "      <td>Intex</td>\n",
+       "      <td>Aqua A2</td>\n",
+       "      <td>1500</td>\n",
+       "      <td>4.00</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>480</td>\n",
+       "      <td>800</td>\n",
+       "      <td>4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>No</td>\n",
+       "      <td>2599</td>\n",
+       "      <td>27649.663226</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1355</th>\n",
+       "      <td>1355</td>\n",
+       "      <td>Videocon Infinium Z51 Nova+</td>\n",
+       "      <td>Videocon</td>\n",
+       "      <td>Infinium Z51 Nova+</td>\n",
+       "      <td>2000</td>\n",
+       "      <td>5.00</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>480</td>\n",
+       "      <td>854</td>\n",
+       "      <td>4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>No</td>\n",
+       "      <td>2940</td>\n",
+       "      <td>30578.211284</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1356</th>\n",
+       "      <td>1356</td>\n",
+       "      <td>Intex Aqua Y4</td>\n",
+       "      <td>Intex</td>\n",
+       "      <td>Aqua Y4</td>\n",
+       "      <td>1700</td>\n",
+       "      <td>4.50</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>480</td>\n",
+       "      <td>854</td>\n",
+       "      <td>2</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>No</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>No</td>\n",
+       "      <td>2999</td>\n",
+       "      <td>27750.249507</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1357</th>\n",
+       "      <td>1357</td>\n",
+       "      <td>iBall Andi4 B20</td>\n",
+       "      <td>iBall</td>\n",
+       "      <td>Andi4 B20</td>\n",
+       "      <td>1250</td>\n",
+       "      <td>4.00</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>480</td>\n",
+       "      <td>800</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.3</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>No</td>\n",
+       "      <td>2498</td>\n",
+       "      <td>26169.615853</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1358</th>\n",
+       "      <td>1358</td>\n",
+       "      <td>iBall Andi Avonte 5</td>\n",
+       "      <td>iBall</td>\n",
+       "      <td>Andi Avonte 5</td>\n",
+       "      <td>2150</td>\n",
+       "      <td>5.00</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>480</td>\n",
+       "      <td>854</td>\n",
+       "      <td>4</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>Android</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Yes</td>\n",
+       "      <td>No</td>\n",
+       "      <td>3999</td>\n",
+       "      <td>30880.178199</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1359 rows × 23 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Unnamed: 0                            Name     Brand  \\\n",
+       "0              0  OnePlus 7T Pro McLaren Edition   OnePlus   \n",
+       "1              1                   Realme X2 Pro    Realme   \n",
+       "2              2               iPhone 11 Pro Max     Apple   \n",
+       "3              3                       iPhone 11     Apple   \n",
+       "4              4                    LG G8X ThinQ        LG   \n",
+       "...          ...                             ...       ...   \n",
+       "1354        1354                   Intex Aqua A2     Intex   \n",
+       "1355        1355     Videocon Infinium Z51 Nova+  Videocon   \n",
+       "1356        1356                   Intex Aqua Y4     Intex   \n",
+       "1357        1357                 iBall Andi4 B20     iBall   \n",
+       "1358        1358             iBall Andi Avonte 5     iBall   \n",
+       "\n",
+       "                       Model  Battery capacity (mAh)  Screen size (inches)  \\\n",
+       "0     7T Pro McLaren Edition                    4085                  6.67   \n",
+       "1                     X2 Pro                    4000                  6.50   \n",
+       "2          iPhone 11 Pro Max                    3969                  6.50   \n",
+       "3                  iPhone 11                    3110                  6.10   \n",
+       "4                  G8X ThinQ                    4000                  6.40   \n",
+       "...                      ...                     ...                   ...   \n",
+       "1354                 Aqua A2                    1500                  4.00   \n",
+       "1355      Infinium Z51 Nova+                    2000                  5.00   \n",
+       "1356                 Aqua Y4                    1700                  4.50   \n",
+       "1357               Andi4 B20                    1250                  4.00   \n",
+       "1358           Andi Avonte 5                    2150                  5.00   \n",
+       "\n",
+       "     Touchscreen  Resolution x  Resolution y  Processor  ...  Front camera  \\\n",
+       "0            Yes          1440          3120          8  ...          16.0   \n",
+       "1            Yes          1080          2400          8  ...          16.0   \n",
+       "2            Yes          1242          2688          6  ...          12.0   \n",
+       "3            Yes           828          1792          6  ...          12.0   \n",
+       "4            Yes          1080          2340          8  ...          32.0   \n",
+       "...          ...           ...           ...        ...  ...           ...   \n",
+       "1354         Yes           480           800          4  ...           0.3   \n",
+       "1355         Yes           480           854          4  ...           5.0   \n",
+       "1356         Yes           480           854          2  ...           2.0   \n",
+       "1357         Yes           480           800          1  ...           0.3   \n",
+       "1358         Yes           480           854          4  ...           0.0   \n",
+       "\n",
+       "      Operating system  Wi-Fi  Bluetooth  GPS Number of SIMs   3G 4G/ LTE  \\\n",
+       "0              Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "1              Android    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "2                  iOS    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "3                  iOS    Yes        Yes  Yes              2  Yes     Yes   \n",
+       "4              Android    Yes        Yes  Yes              1   No      No   \n",
+       "...                ...    ...        ...  ...            ...  ...     ...   \n",
+       "1354           Android    Yes        Yes  Yes              2  Yes      No   \n",
+       "1355           Android    Yes        Yes  Yes              2  Yes      No   \n",
+       "1356           Android    Yes        Yes   No              2  Yes      No   \n",
+       "1357           Android    Yes        Yes  Yes              2  Yes      No   \n",
+       "1358           Android    Yes        Yes  Yes              2  Yes      No   \n",
+       "\n",
+       "       Price Predicted Price  \n",
+       "0      58998    75000.000000  \n",
+       "1      27999    55792.501783  \n",
+       "2     106900    46614.283392  \n",
+       "3      62900    40755.459206  \n",
+       "4      49990    55792.501783  \n",
+       "...      ...             ...  \n",
+       "1354    2599    27649.663226  \n",
+       "1355    2940    30578.211284  \n",
+       "1356    2999    27750.249507  \n",
+       "1357    2498    26169.615853  \n",
+       "1358    3999    30880.178199  \n",
+       "\n",
+       "[1359 rows x 23 columns]"
+      ]
+     },
+     "execution_count": 135,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result_test = data_test.copy()\n",
+    "\n",
+    "result_test[\"Predicted Price\"] = result_test.apply(fuzzy_pred, axis=1)\n",
+    "\n",
+    "result_test"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Оценка результатов на основе метрик для задачи регрессии**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 138,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'RMSE_train': 28568.780129367737,\n",
+       " 'RMSE_test': 28568.780129367737,\n",
+       " 'RMAE_test': 165.28156612336826,\n",
+       " 'R2_test': -3.2533731852277636}"
+      ]
+     },
+     "execution_count": 138,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import math\n",
+    "from sklearn import metrics\n",
+    "\n",
+    "rmetrics = {}\n",
+    "\n",
+    "rmetrics[\"RMSE_train\"] = math.sqrt(\n",
+    "    metrics.mean_squared_error(result_train[\"Price\"], result_train[\"Predicted Price\"])\n",
+    ")\n",
+    "\n",
+    "rmetrics[\"RMSE_test\"] = math.sqrt(\n",
+    "    metrics.mean_squared_error(result_test[\"Price\"], result_test[\"Predicted Price\"])\n",
+    ")\n",
+    "\n",
+    "rmetrics[\"RMAE_test\"] = math.sqrt(\n",
+    "    metrics.mean_absolute_error(result_test[\"Price\"], result_test[\"Predicted Price\"])\n",
+    ")\n",
+    "\n",
+    "rmetrics[\"R2_test\"] = metrics.r2_score(\n",
+    "    result_test[\"Price\"], result_test[\"Predicted Price\"]\n",
+    ")\n",
+    "\n",
+    "rmetrics"
+   ]
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "aimenv",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.5"
   }
  },
  "nbformat": 4,