linear-regression/fish/fish-linear-regression-model.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "bronze-singer",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sbn\n",
    "\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import metrics\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "lesser-training",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing Fish dataset from CSV file\n",
    "fish = pd.read_csv(\"Fish_dataset.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "supported-airplane",
   "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>Species</th>\n",
       "      <th>Weight</th>\n",
       "      <th>Length1</th>\n",
       "      <th>Length2</th>\n",
       "      <th>Length3</th>\n",
       "      <th>Height</th>\n",
       "      <th>Width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Bream</td>\n",
       "      <td>242.0</td>\n",
       "      <td>23.2</td>\n",
       "      <td>25.4</td>\n",
       "      <td>30.0</td>\n",
       "      <td>11.5200</td>\n",
       "      <td>4.0200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Bream</td>\n",
       "      <td>290.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>26.3</td>\n",
       "      <td>31.2</td>\n",
       "      <td>12.4800</td>\n",
       "      <td>4.3056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Bream</td>\n",
       "      <td>340.0</td>\n",
       "      <td>23.9</td>\n",
       "      <td>26.5</td>\n",
       "      <td>31.1</td>\n",
       "      <td>12.3778</td>\n",
       "      <td>4.6961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Bream</td>\n",
       "      <td>363.0</td>\n",
       "      <td>26.3</td>\n",
       "      <td>29.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>12.7300</td>\n",
       "      <td>4.4555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Bream</td>\n",
       "      <td>430.0</td>\n",
       "      <td>26.5</td>\n",
       "      <td>29.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>12.4440</td>\n",
       "      <td>5.1340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Species  Weight  Length1  Length2  Length3   Height   Width\n",
       "0   Bream   242.0     23.2     25.4     30.0  11.5200  4.0200\n",
       "1   Bream   290.0     24.0     26.3     31.2  12.4800  4.3056\n",
       "2   Bream   340.0     23.9     26.5     31.1  12.3778  4.6961\n",
       "3   Bream   363.0     26.3     29.0     33.5  12.7300  4.4555\n",
       "4   Bream   430.0     26.5     29.0     34.0  12.4440  5.1340"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test\n",
    "fish.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "consecutive-liberty",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Task 1 : Plot a bar chart showing count of individual species.\n",
    "fish['Species'].value_counts().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "cloudy-disability",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Task 2 : Identify outliers and remove if any.\n",
    "plt.subplot(3,2,1)\n",
    "sbn.boxplot(fish['Weight'])\n",
    "plt.subplot(3,2,2)\n",
    "sbn.boxplot(fish['Length1'])\n",
    "plt.subplot(3,2,3)\n",
    "sbn.boxplot(fish['Length2'])\n",
    "plt.subplot(3,2,4)\n",
    "sbn.boxplot(fish['Length3'])\n",
    "plt.subplot(3,2,5)\n",
    "sbn.boxplot(fish['Height'])\n",
    "plt.subplot(3,2,6)\n",
    "sbn.boxplot(fish['Width'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "powered-longer",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Outliers Present : Weight , Length1 , Length2 , Length3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "electronic-withdrawal",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Funtion to generate summary report\n",
    "def var_summary(x):\n",
    "    return pd.Series([x.count(), x.isnull().sum(), x.sum(), x.mean(), x.median(),  x.std(), x.var(), x.min(), x.quantile(0.01), x.quantile(0.05),x.quantile(0.10),x.quantile(0.25),x.quantile(0.50),x.quantile(0.75), x.quantile(0.90),x.quantile(0.95), x.quantile(0.99),x.max()], \n",
    "                  index=['N', 'NMISS', 'SUM', 'MEAN','MEDIAN', 'STD', 'VAR', 'MIN', 'P1' , 'P5' ,'P10' ,'P25' ,'P50' ,'P75' ,'P90' ,'P95' ,'P99' ,'MAX'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "aggressive-constitution",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Removing Target Variable : Species\n",
    "fish_new = fish.iloc[:,1:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "religious-platform",
   "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>Weight</th>\n",
       "      <th>Length1</th>\n",
       "      <th>Length2</th>\n",
       "      <th>Length3</th>\n",
       "      <th>Height</th>\n",
       "      <th>Width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>242.0</td>\n",
       "      <td>23.2</td>\n",
       "      <td>25.4</td>\n",
       "      <td>30.0</td>\n",
       "      <td>11.5200</td>\n",
       "      <td>4.0200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>290.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>26.3</td>\n",
       "      <td>31.2</td>\n",
       "      <td>12.4800</td>\n",
       "      <td>4.3056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>340.0</td>\n",
       "      <td>23.9</td>\n",
       "      <td>26.5</td>\n",
       "      <td>31.1</td>\n",
       "      <td>12.3778</td>\n",
       "      <td>4.6961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>363.0</td>\n",
       "      <td>26.3</td>\n",
       "      <td>29.0</td>\n",
       "      <td>33.5</td>\n",
       "      <td>12.7300</td>\n",
       "      <td>4.4555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>430.0</td>\n",
       "      <td>26.5</td>\n",
       "      <td>29.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>12.4440</td>\n",
       "      <td>5.1340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Weight  Length1  Length2  Length3   Height   Width\n",
       "0   242.0     23.2     25.4     30.0  11.5200  4.0200\n",
       "1   290.0     24.0     26.3     31.2  12.4800  4.3056\n",
       "2   340.0     23.9     26.5     31.1  12.3778  4.6961\n",
       "3   363.0     26.3     29.0     33.5  12.7300  4.4555\n",
       "4   430.0     26.5     29.0     34.0  12.4440  5.1340"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test\n",
    "fish_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "prospective-magazine",
   "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>N</th>\n",
       "      <th>NMISS</th>\n",
       "      <th>SUM</th>\n",
       "      <th>MEAN</th>\n",
       "      <th>MEDIAN</th>\n",
       "      <th>STD</th>\n",
       "      <th>VAR</th>\n",
       "      <th>MIN</th>\n",
       "      <th>P1</th>\n",
       "      <th>P5</th>\n",
       "      <th>P10</th>\n",
       "      <th>P25</th>\n",
       "      <th>P50</th>\n",
       "      <th>P75</th>\n",
       "      <th>P90</th>\n",
       "      <th>P95</th>\n",
       "      <th>P99</th>\n",
       "      <th>MAX</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Weight</th>\n",
       "      <td>159.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>63333.9000</td>\n",
       "      <td>398.326415</td>\n",
       "      <td>273.0000</td>\n",
       "      <td>357.978317</td>\n",
       "      <td>128148.475121</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>6.364000</td>\n",
       "      <td>9.80000</td>\n",
       "      <td>29.58000</td>\n",
       "      <td>120.00000</td>\n",
       "      <td>273.0000</td>\n",
       "      <td>650.0000</td>\n",
       "      <td>930.0000</td>\n",
       "      <td>1000.00000</td>\n",
       "      <td>1571.000000</td>\n",
       "      <td>1650.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Length1</th>\n",
       "      <td>159.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4173.3000</td>\n",
       "      <td>26.247170</td>\n",
       "      <td>25.2000</td>\n",
       "      <td>9.996441</td>\n",
       "      <td>99.928837</td>\n",
       "      <td>7.5000</td>\n",
       "      <td>9.706000</td>\n",
       "      <td>11.30000</td>\n",
       "      <td>13.44000</td>\n",
       "      <td>19.05000</td>\n",
       "      <td>25.2000</td>\n",
       "      <td>32.7000</td>\n",
       "      <td>38.2000</td>\n",
       "      <td>41.19000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>59.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Length2</th>\n",
       "      <td>159.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4518.1000</td>\n",
       "      <td>28.415723</td>\n",
       "      <td>27.3000</td>\n",
       "      <td>10.716328</td>\n",
       "      <td>114.839688</td>\n",
       "      <td>8.4000</td>\n",
       "      <td>10.206000</td>\n",
       "      <td>11.80000</td>\n",
       "      <td>14.62000</td>\n",
       "      <td>21.00000</td>\n",
       "      <td>27.3000</td>\n",
       "      <td>35.5000</td>\n",
       "      <td>41.2000</td>\n",
       "      <td>44.10000</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>63.400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Length3</th>\n",
       "      <td>159.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4965.1000</td>\n",
       "      <td>31.227044</td>\n",
       "      <td>29.4000</td>\n",
       "      <td>11.610246</td>\n",
       "      <td>134.797808</td>\n",
       "      <td>8.8000</td>\n",
       "      <td>11.264000</td>\n",
       "      <td>13.10000</td>\n",
       "      <td>16.16000</td>\n",
       "      <td>23.15000</td>\n",
       "      <td>29.4000</td>\n",
       "      <td>39.6500</td>\n",
       "      <td>45.3400</td>\n",
       "      <td>46.74000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>68.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Height</th>\n",
       "      <td>159.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1426.3880</td>\n",
       "      <td>8.970994</td>\n",
       "      <td>7.7860</td>\n",
       "      <td>4.286208</td>\n",
       "      <td>18.371576</td>\n",
       "      <td>1.7284</td>\n",
       "      <td>1.874056</td>\n",
       "      <td>2.20356</td>\n",
       "      <td>3.76480</td>\n",
       "      <td>5.94480</td>\n",
       "      <td>7.7860</td>\n",
       "      <td>12.3659</td>\n",
       "      <td>15.1904</td>\n",
       "      <td>16.37732</td>\n",
       "      <td>18.685296</td>\n",
       "      <td>18.957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Width</th>\n",
       "      <td>159.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>702.3802</td>\n",
       "      <td>4.417486</td>\n",
       "      <td>4.2485</td>\n",
       "      <td>1.685804</td>\n",
       "      <td>2.841935</td>\n",
       "      <td>1.0476</td>\n",
       "      <td>1.148400</td>\n",
       "      <td>1.28314</td>\n",
       "      <td>2.22784</td>\n",
       "      <td>3.38565</td>\n",
       "      <td>4.2485</td>\n",
       "      <td>5.5845</td>\n",
       "      <td>6.7421</td>\n",
       "      <td>7.28462</td>\n",
       "      <td>7.679758</td>\n",
       "      <td>8.142</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             N  NMISS         SUM        MEAN    MEDIAN         STD  \\\n",
       "Weight   159.0    0.0  63333.9000  398.326415  273.0000  357.978317   \n",
       "Length1  159.0    0.0   4173.3000   26.247170   25.2000    9.996441   \n",
       "Length2  159.0    0.0   4518.1000   28.415723   27.3000   10.716328   \n",
       "Length3  159.0    0.0   4965.1000   31.227044   29.4000   11.610246   \n",
       "Height   159.0    0.0   1426.3880    8.970994    7.7860    4.286208   \n",
       "Width    159.0    0.0    702.3802    4.417486    4.2485    1.685804   \n",
       "\n",
       "                   VAR     MIN         P1        P5       P10        P25  \\\n",
       "Weight   128148.475121  0.0000   6.364000   9.80000  29.58000  120.00000   \n",
       "Length1      99.928837  7.5000   9.706000  11.30000  13.44000   19.05000   \n",
       "Length2     114.839688  8.4000  10.206000  11.80000  14.62000   21.00000   \n",
       "Length3     134.797808  8.8000  11.264000  13.10000  16.16000   23.15000   \n",
       "Height       18.371576  1.7284   1.874056   2.20356   3.76480    5.94480   \n",
       "Width         2.841935  1.0476   1.148400   1.28314   2.22784    3.38565   \n",
       "\n",
       "              P50       P75       P90         P95          P99       MAX  \n",
       "Weight   273.0000  650.0000  930.0000  1000.00000  1571.000000  1650.000  \n",
       "Length1   25.2000   32.7000   38.2000    41.19000    56.000000    59.000  \n",
       "Length2   27.3000   35.5000   41.2000    44.10000    60.000000    63.400  \n",
       "Length3   29.4000   39.6500   45.3400    46.74000    64.000000    68.000  \n",
       "Height     7.7860   12.3659   15.1904    16.37732    18.685296    18.957  \n",
       "Width      4.2485    5.5845    6.7421     7.28462     7.679758     8.142  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Getting Summary Report of altered fish dataset\n",
    "fish_new.apply(lambda x:var_summary(x)).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "several-escape",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clipping Data Outliers from fields : Weight , Length1, Length2, Length3\n",
    "fish_new['Weight']=fish_new['Weight'].clip(fish_new['Weight'].quantile(0.01),fish_new['Weight'].quantile(0.99))\n",
    "fish_new['Length1']=fish_new['Length1'].clip(fish_new['Length1'].quantile(0.01),fish_new['Length1'].quantile(0.99))\n",
    "fish_new['Length2']=fish_new['Length2'].clip(fish_new['Length2'].quantile(0.01),fish_new['Length2'].quantile(0.99))\n",
    "fish_new['Length3']=fish_new['Length3'].clip(fish_new['Length3'].quantile(0.01),fish_new['Length3'].quantile(0.99))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "outdoor-accused",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Weight', ylabel='Density'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : Weight\n",
    "sbn.distplot(fish_new['Weight'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "partial-fraud",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Length1', ylabel='Density'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : Length1\n",
    "sbn.distplot(fish_new['Length1'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "temporal-isaac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Length2', ylabel='Density'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEGCAYAAAB/+QKOAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAAsXUlEQVR4nO3dd3hc9Z33/fdXo96t5qJi2Za7jZvcsIFQQwsOwYSakIQsea6ETbtzZ0k2y5Ls3vskefYKd/IQuCELCSG0GAI4dDAtFBe54t7kItmy1WX19rv/mHFWiLEt2zM6I+nzuq65NHPOmdHHGnm+Or/zK+acQ0REpLcorwOIiEhkUoEQEZGgVCBERCQoFQgREQlKBUJERIKK9jpAqGRlZbnCwkKvY4iIDChr166tcs5lB9s3aApEYWEhJSUlXscQERlQzGz/ifapiUlERIJSgRARkaBUIEREJCgVCBERCUoFQkREglKBEBGRoFQgREQkKBUIEREJSgVCRESCGjQjqSXyPbHqQMhf8+b5BSF/TRHx0xmEiIgEpQIhIiJBqUCIiEhQKhAiIhKUCoSIiASlAiEiIkGpQIiISFAqECIiEpQKhIiIBKUCISIiQYW1QJjZ5Wa2w8x2m9ldQfbHmdnTgf2rzKyw1/4CM2s0sx+EM6eIiHxa2AqEmfmA3wJXAFOAm8xsSq/DbgdqnXNFwL3AL3rt/xXwSrgyiojIiYXzDGIesNs5t9c51w48BSzpdcwS4NHA/WeAi83MAMzs80ApsCWMGUVE5ATCWSBygYM9HpcFtgU9xjnXCdQDmWaWDPwT8NOTfQMzu8PMSsyspLKyMmTBRUQkci9S3wPc65xrPNlBzrmHnHPFzrni7Ozs/kkmIjJEhHM9iHIgv8fjvMC2YMeUmVk0kAZUA/OBpWb2SyAd6DazVufcfWHMKyIiPYSzQKwBxpvZGPyF4Ebg5l7HLAduAz4ClgJvOecccN7xA8zsHqBRxUFEpH+FrUA45zrN7E7gNcAHPOKc22JmPwNKnHPLgYeBx8xsN1CDv4iIiEgECOuSo865l4GXe227u8f9VuD6U7zGPWEJJyIiJxWpF6lFRMRjKhAiIhKUCoSIiASlAiEiIkGpQIiISFAqECIiEpQKhIiIBKUCISIiQalAiIhIUCoQIiISlAqEiIgEpQIhIiJBqUCIiEhQKhAiIhJUWKf7FjkbLe1dNLV1EhcTRUp8jNdxRIYcFQiJKM45Pi6v571dlRyua8UFtmclxzIjP53F47KIi/F5mlFkqFCBkIjR0t7FE6v3s6eyiRGp8Vw8OYeMpFga27rYWXGMFduOsnJvDdfOHMWUUWlexxUZ9FQgJCI0tHTw8Ael1DS2s2TmKOYWZhBl9vf9i4uyOFjTzPKNh/jTqgOcNz6Lz04d4WFikcFPF6nFc+2d3Ty2cj/1LR18dVEh88dkfqI4HJefkcg3zh/LvDEZ/G1XFc+uLaOzq9uDxCJDgwqEeMo5x1/Wl3GoroUbi/MZm5180uOjfVEsmTGKSyYPZ/3BOn747Caccyd9joicGTUxiac2ldezqayey6YMZ9LI1D49x8y4aFIODsdf1pUzKi2BH3x2YpiTigw9KhDimca2Tv668RD5wxI4f0L2aT//ook55KTEcd/buxmRFs+tC0aHIaXI0KUCIZ55Y2sFbR3dfGF2XtBrDqdiZvzbkmkcaWjj7hc2MzItnosnDw9DUpGhSdcgxBMVDa2U7KtlwdgMhqfGn/HrRPuiuO/mWUwdlcZ3ntrA7qPHQphSZGhTgRBPvLa5griYKC6cmHPWr5UYG82DX5pDfEwU//DHtdS3dIQgoYioQEi/K6ttZseRY1wwIYfEuNC0co5KT+CBW+dQVtvMt59cT1e3ejaJnC0VCOl3b++oJCHGx4IxGSF93bmFGfz0mmm8u7OSX762PaSvLTIUqUBIv6poaGXb4QYWjssMy5xKN88v4NYFBTz47l5e2FAe8tcXGUrUi0n61Qe7qojxGeeOywzb97j76qnsrGjkh89sYlx2MtNyT2/epidWHQh5ppvnF4T8NUXCTWcQ0m8a2zrZWFbH7IJhJMaG72+T2Ogo7r91NplJsdzxxxKqGtvC9r1EBjMVCOk3Jftq6Ox2LBgbvrOH47KS43joy8XUNLfzzT+to71TczaJnC4VCOkXXd2OVaU1FOUkn9W4h9MxLTeNX1x3Dqv31fCzF7f0y/cUGUxUIKRfvLerkvqWDuYVhrbn0qksmZnLNy4Yy59WHgjLtQWRwUwFQvrFMyVlJMb6mDQypd+/9w8/O4kLJmTzr8s3s7q0pt+/v8hApQIhYVfX3M4bW48wMz+d6Kj+/5XzRRm/uXEW+cMSuf0Pa9hwsK7fM4gMROrmKmH3woZDtHd1M7tgWMhf+3SajZbOyeO/3i/lhgc/4muLxpCfkRjyPCKDic4gJOyWrT3IlJGpjEpP8DRHemIsX188hqS4aB75oJQDNc2e5hGJdCoQElbbDjewubyB64vzvI4CfLJIPPz+XjaX13sdSSRiqUBIWC0rKSPGZyyZmet1lL9LT4zlG+ePZURqPE+sPsDrWyo0uZ9IEGEtEGZ2uZntMLPdZnZXkP1xZvZ0YP8qMysMbJ9nZhsCt41mdm04c0p4dHR18/yGci6ZPJyMpFiv43xCSnwMXz9vLMWjh/HOzkoeem8PRxpavY4lElHCViDMzAf8FrgCmALcZGZTeh12O1DrnCsC7gV+Edi+GSh2zs0ELgceNDNdUB9g3t9dRU1TO9fOipyzh55ifFF8YXYeN8zNp7qpnfve2s2Lmw7R2NbpdTSRiBDOD915wG7n3F4AM3sKWAJs7XHMEuCewP1ngPvMzJxzPa8exgM6/x+AXtx4mJT4aC6YePrrTfenGXnpjMtO5vUtFXy0p5rVpTWck5fOgrEZ5A1TTycZusJZIHKBgz0elwHzT3SMc67TzOqBTKDKzOYDjwCjgS855z71Z52Z3QHcAVBQoNkyI0lrRxevb6ngs9NGEBcd+mm9Qy05LpovzM5j8fgsPtpTzfqDdaw7UMuI1Hgmjkhh4vAU8jMS8UWd/trZIgNVxDbbOOdWAVPNbDLwqJm94pxr7XXMQ8BDAMXFxTrLiCDv7qzkWFsnn5sxyusopyUnJZ4lM3P57NQRbDhYx8fl9fxtVyXv7qwkLjqKMVlJjMlKYmx2MiPT4okyFQwZvMJZIMqB/B6P8wLbgh1TFrjGkAZU9zzAObfNzBqBaUBJ+OJKKP114yEykmLDuu5DOMXH+FgwNpMFYzNp7ehi19FGdh9tpLSqke0VxwLHRFGYmcTYQMEYoYIhg0w4C8QaYLyZjcFfCG4Ebu51zHLgNuAjYCnwlnPOBZ5zMNDsNBqYBOwLY1YJoeb2TlZsO8oXZucS4xv4PanjY3xMz01jemDhofqWDkqrmiitamRvZdPfC8awxBiKCzOYUzCM1IQYLyOLhETYCkTgw/1O4DXABzzinNtiZj8DSpxzy4GHgcfMbDdQg7+IACwG7jKzDqAb+KZzripcWSW0Vmw7SktH14BrXuqrtIQYZuanMzM/HfAXjD1HG1l3sJY3th5hxbYjTM9N4+LJw8lKjvM2rMhZCOs1COfcy8DLvbbd3eN+K3B9kOc9BjwWzmwSPn/deIiclDjm9vPU3l5JS4hh9uhhzB49jKrGNlaX1rCqtJqPy+tZXJTFRZOGex1R5IxE7EVqGZiOtXbwzs5KbplfMCR7/GQlx3Hl9JGcNz6L17ce4b1dVWw51MCc0cOYnnd6a2OLeG3gNxBLRHlz2xHaO7u5+pyRXkfxVEp8DNfNzuPri8fQ2e34wgMf8PQaLVgkA4sKhITUS5sqGJkWz6z80E/tPRCNzU7mHy8qYsHYTP7p2Y/5xavbcU49smVgUIGQkGlo7eC9nZVcMW0kUUOweelEEmOj+f1X5nLTvAIeeGcP/7p8C92aHFAGAF2DkJBZse0I7V3dXHXOCK+jRJxoXxT/ce00kuN8/O5vpcT4ovjJVZMxjZuQCKYCISGj5qUTO77yXWFmEgvHZfLw+6WU1TRzwcScM37Nm+drehkJLzUxSUioealvzIyrpo/knLw0Xtt6hC2HtGCRRC4VCAkJNS/1XZQZ183OI39YAstKyqio1zoUEplUICQk1Lx0emJ8UdyyYDRx0VE8ufoAbZ1dXkcS+RQVCDlral46M6nxMXxxbj5VjW38deNhr+OIfIoKhJw1NS+duXHZyVwwMZt1B2rZXtHgdRyRT1CBkLOm5qWzc9HEHHJS4nh+fTmtHWpqksihAiFn5Zial85atC+K62bncay1k1e3VHgdR+TvVCDkrLyp5qWQyM9IZFFRFqtLa9hb2eh1HBGgjwXCzP5iZleZmQqKfIKal0LnksnDyUiK5bn15XR2dXsdR6TPZxD3418NbpeZ/dzMJoYxkwwQal4KrdjoKK6ZMYrqpnZW7q0+9RNEwqxPBcI596Zz7hZgNv6lP980sw/N7KtmprUVhyg1L4XehOEpjM9J5q0dR2lu6/Q6jgxxfW4yMrNM4CvA14H1wK/xF4w3wpJMIp6al8Ljiukjaevo5q0dR72OIkNcX69BPAf8DUgEPuecu8Y597Rz7h+B5HAGlMh0rLWD93apeSkcRqTGU1yYwcq91VQda/M6jgxhfT2D+J1zbopz7v91zh0GMLM4AOdccdjSScR6bYt/5birhvjKceFyyeQcon1R6vYqnuprgfj3INs+CmUQGVhe2FBOQUYiswvSvY4yKKXEx3D++Gy2Hm7gYE2z13FkiDppgTCzEWY2B0gws1lmNjtw+wz+5iYZgo4ea+WD3VUsmTlKC96E0aJxmSTE+Hhru65FiDdOtWDQZ/FfmM4DftVj+zHgx2HKJBHurxsP0+1gycxcr6MManExPhaPz+KNrUcoq20mb5j+JpP+ddIC4Zx7FHjUzK5zzj3bT5nkDBxfsSyUTrRi2QsbypmWm0pRjvonhNvCsZm8v6uKt7Yf5csLC72OI0PMSQuEmd3qnPsTUGhm3++93zn3qyBPk0FsT2Ujm8rq+clVk72OMiTEx/hYVJTJm9uOUl7XQm56gteRZAg51UXqpMDXZCAlyE2GmBfWl2MGn5sxyusoQ8a547KIj4nStQjpd6dqYnow8PWn/RNHIplzjuc3HOLccZkMT433Os6QER/jY9G4LFZsP8qRhlb97KXf9HWg3C/NLNXMYsxshZlVmtmt4Q4nkWXdgToO1DTr4rQHFo7NJMZnvL+7yusoMoT0dRzEZc65BuBq/HMxFQH/M1yhJDItKzlIQoyPK6Zp7qX+lhgXzeyCYWw4WMex1g6v48gQ0dcCcbwp6ipgmXOuPkx5JEI1tnWyfOMhPjdjJCnxmp/RC4uKsujudprpVfpNXwvEi2a2HZgDrDCzbKA1fLEk0ry06RDN7V3cMDd411cJv6zkOCaNTGVVaQ3tnVovQsKvr9N93wWcCxQ75zqAJmBJOINJZHlqzUHG5yRrag2PLS7Korm9i3UHar2OIkPAqUZS9zQJ/3iIns/5Y4jzSATaUXGM9Qfq+MlVkzW1hscKMxPJG5bAB7ur6Op2+DSTroRRX3sxPQb8J7AYmBu4aRbXIeLpNQeJ8RnXzlLvJa+ZGYuKsqhuaue9nZVex5FBrq9nEMXAFOecC2cYiTxtnV08t76My6aMIDM5zus4AkwdlUpKXDR//GgfF07K8TqODGJ9vUi9GVDfxiHo1c0V1DZ38MW5+V5HkYDoqCiKCzN4Z2clB6o1FbiET18LRBaw1cxeM7Plx2/hDCaR4fcf7GNMVhLnFWV5HUV6mDcmgygzHl+13+soMoj1tYnpnnCGkMi0/kAtGw7Wcc/npmhZ0QiTlhDDpZOH83TJQb536QTiY3xeR5JBqK/dXN/FP4I6JnB/DbAujLkkAvzhw32kxEWztFjNS5HoywtHU9fcwYubDnsdRQapvvZi+gfgGeDBwKZc4Pk+PO9yM9thZrvN7K4g++PM7OnA/lVmVhjYfqmZrTWzjwNfL+rrP0hCo6Glg5c2Heb64nyS406nN7T0l4XjMhmXncRjK9XMJOHR12sQ3wIWAQ0AzrldwEm7T5iZD/gtcAUwBbjJzKb0Oux2oNY5VwTcC/wisL0K+JxzbjpwG/BYH3NKiKwqrabLOb5ybqHXUeQEzIwvLRjNxoN1fFym2W8k9PpaINqcc+3HHwQGy52qy+s8YLdzbm/guU/x6dHXS4BHA/efAS42M3POrXfOHQps34J/TWz1sewnHV3drC6t4eJJwynI1DKXkezaWXnERUfxdEnoVxQU6WuBeNfMfoz/g/pSYBnw11M8Jxc42ONxWWBb0GOcc51APZDZ65jrgHXOubbe38DM7jCzEjMrqazUoKFQ2XCwjqb2Lr62qNDrKHIKaYkxXDFtBC9sOERrR5fXcWSQ6WuBuAuoBD4GvgG8DPwkXKGOM7Op+JudvhFsv3PuIedcsXOuODs7O9xxhoSubsd7OyvJTU9g4bjetVoi0Q1zCzjW2skrm3WxWkKrr72YuvFflP6mc26pc+53fRhVXQ707P6SF9gW9JhAs1UaUB14nAc8B3zZObenLznl7G0ur6e6qZ0LJmRr3qUBYsHYDEZnJvLU6oOnPljkNJy0QJjfPWZWBewAdgRWk7u7D6+9BhhvZmPMLBa4Eeg9uG45/ovQAEuBt5xzzszSgZeAu5xzH5zGv0fOQrdzvLPzKDkpcUwZlep1HOkjM+OLxfmsKq2htKrJ6zgyiJzqDOJ7+HsvzXXOZTjnMoD5wCIz+97Jnhi4pnAn8BqwDfizc26Lmf3MzK4JHPYwkGlmu4Hv42/KIvC8IuBuM9sQuGnSmTDbfvgYRxrauGBCNlE6exhQls7JI8rgzyU6i5DQsZO1FJnZeuBS51xVr+3ZwOvOuVlhztdnxcXFrqSkxOsYnnli1dn1YnHO8cC7e2hu7+J7l0zQNNIDwM3zP7l409cfXcPGsno+uusion19vbwoQ52ZrXXOBZ2d+1S/RTG9iwOAc64S0LqTg8juykbKals4f3y2isMA9cXifCqPtfH2DvXok9A4VYFoP8N9MoA453hj6xHSEmK0YtwAduGkHLJT4nh6jZqZJDROVSBmmFlDkNsxYHp/BJTw23a4gbLaFi6elKOmiQEsxhfFdbPzeHvHUY42aMl4OXsn/TRwzvmcc6lBbinOOTUxDQLdzvH61iNkJccyq2CY13HkLN0wN5+ubscz68q8jiKDgP5cHOI2Hqzj6LE2Lpk8XNceBoExWUnMG5PBspIytACknC0ViCGss7ubN7cdYVRaPNNy07yOIyFy/Zw8SquaWHeg1usoMsCpQAxha/bVUtvcwWVTR2jcwyBy5fSRJMb6WFaiZiY5OyoQQ1R7Zzdvbz9KYWYS43OSvY4jIZQUF82V00fy4qbDtLRrAj85cyoQQ9RHe6pobOvks1OHa86lQWjpnDwa2zp5bUuF11FkAFOBGIJa2rt4d1clk0akMDozyes4EgbzCjMoyEhk2VqNiZAzpwIxBL23q5LWjm4unTLc6ygSJlFRxnWz8/hwTzVltc1ex5EBSgViiDnW2sGHe6o4Jy+NkWkJXseRMPrC7Fycg+fW9Z5lX6RvVCCGmLd3VNLV7bh0ss4eBrv8jETOHZfJM+s0JkLOjArEEFLb1M6a0hrmjM4gM1lLfA8FS+fksb+6mTX7NCZCTp8KxBCyYvtRzOCiSVpaY6i4fNoIkuOiWaZ1IuQMqEAMEUcbWll/oJYFYzNJS9A0WkNFYmw0V00fyUsfH6aprdPrODLAqEAMEW9uP0pMdBTnT8j2Oor0s6XFeTS3d/HqZo2JkNOjAjEElNe1sLm8nsVFWSTHRXsdR/pZ8ehhFGZqTIScPhWIIeCNrRUkxPhYXJTldRTxgJmxdE4eK/fWcLBGYyKk71QgBrnSqiZ2HmnkggnZxMf4vI4jHvnC7DzM4FmtEyGnQQViEPMvJVpBSlw0C8Zmeh1HPDQqPYHFRVk8s7aM7m6NiZC+UYEYxPZUNrGvupnPTMohNlpv9VC3dE4eZbUtrCqt8TqKDBD61BjE3tp+hNT4aOaO1lKiApdNGUFKXDTPrFUzk/SNCsQgtbeqkX3VzZw/IZton95mgYRYH1fPGMXLHx+mUWMipA/U53GQenv7UZLjoplbmOF1FAmTJ1YdOO3npMVH09LRxb++sJk5oz/5u3Hz/IJQRZNBQn9aDkL7q5vYU9nEeeOziNHZg/SQn5FIVnIca/fXeR1FBgB9egxCb+84SmKsj/lj1HNJPsnMmFOQzr7qJqob27yOIxFOBWKQKa9rYeeRRhYXZannkgQ1s2AYBqw7UOd1FIlw+gQZZD7YXUVsdJTGPcgJpSXEUJSTzPoDtXRrnQg5CRWIQaS+pYNNZXXMHT1Mo6blpOaMHkZdSwd7K5u8jiIRTAViEFm5txrnYOE4zbkkJzd5ZCrxMVGsO6CFhOTEVCAGibbOLlaVVjN1VCoZSbFex5EIF+OLYkZeOlsO1dPa0eV1HIlQKhCDxLoDdbR2dLNIM7ZKH80uGEZHl+Pj8nqvo0iEUoEYBLq6HR/uriJ/WAIFGYlex5EBIm9YAtkpcazbr2YmCU4FYhBYse0I1U3tLCrKwsy8jiMDhH9MxDD21zRTdUxjIuTTVCAGgYffLyU9IYapo9K8jiIDzMyC9MCYCJ1FyKepQAxwH5fVs6q0hoXjMvFF6exBTk9qfAwThqew7kAtXVonQnpRgRjgHn5/L0mxPk3KJ2dszuhhNLR28vb2o15HkQijAjGAVdS38uKmw9wwt0AD4+SMTR6ZSmp8NI+t3O91FIkwYS0QZna5me0ws91mdleQ/XFm9nRg/yozKwxszzSzt82s0czuC2fGgezRj/bR7RxfXVTodRQZwHxRRnFhBu/tquRAdbPXcSSChK1AmJkP+C1wBTAFuMnMpvQ67Hag1jlXBNwL/CKwvRX4F+AH4co30DW1dfL4yv1cPm0E+eraKmdpbmEGUWY8vlpnEfLfwnkGMQ/Y7Zzb65xrB54ClvQ6ZgnwaOD+M8DFZmbOuSbn3Pv4C4UE8ey6MhpaO7l98Rivo8ggkJYQwyWTc1hWUkZbp0ZWi184C0QucLDH47LAtqDHOOc6gXpA05CeQne345H3S5mZn87sAq03LaFx64LR1DS188rHFV5HkQgxoC9Sm9kdZlZiZiWVlZVex+k3K7YfZV91M18/b4wGxknILBqXRWFmIn/SxWoJCGeBKAfyezzOC2wLeoyZRQNpQHVfv4Fz7iHnXLFzrjg7O/ss4w4c//W3veSmJ3D51BFeR5FBJCrKuHXBaEr217JZ8zMJ4S0Qa4DxZjbGzGKBG4HlvY5ZDtwWuL8UeMs5rWByMscHxn3l3EKitd60hNj1xfkkxfp45P1Sr6NIBAjbJ0zgmsKdwGvANuDPzrktZvYzM7smcNjDQKaZ7Qa+D/y9K6yZ7QN+BXzFzMqC9IAako4PjLthXv6pDxY5TWkJMXxxbj7LNx6iol59RIa66HC+uHPuZeDlXtvu7nG/Fbj+BM8tDGe2gej4wLgvLywkNT7G6zgySH313DE8+uE+/vjRPn54+SSv44iH1EYxgGhgnPSHgsxEPjt1BI+vOkBze6fXccRDKhADhAbGSX/6+nljqG/p4Nm1ZV5HEQ+pQAwQGhgn/Wl2wTBm5qfz8PuldGuW1yFLBWIA0MA46W9mxj+cN5Z91c28slkD54YqFYgBQAPjxAuXTxvBuOwkfrNil84ihigViAFAA+PEC74o49sXj2fHkWO8tkVnEUORCkSE21yugXHinavPGcXYrCR+rbOIIUmfOBHuwff2khwXrYFx4glflHHnRUVsrzjG61uPeB1H+pkKRAQ7WNPMS5sOccv8Ag2ME89cM2MUhZmJ/GbFLjQTztCiAhHBfve3vfiijK8uUtdW8U60L4o7LxrP1sMNvPTxYa/jSD9SgYhQ1Y1t/LnkINfOymVEWrzXcWSIu3ZWLpNGpPDzV7bT2qEFhYYKFYgI9ehH+2nt6OaO88d6HUUEX5Txk6umUFbbwu8/2Od1HOknKhARqLm9kz9+tI9LpwynKCfF6zgiACwen8XFk3L47du7qWps8zqO9AMViAj05OqD1DV38P9coLMHiSw/vmoyrR1d/OqNnV5HkX6gAhFhWtq7+D/v7mHB2AzmjM7wOo7IJ4zLTubWBaN5avUBthzSqnODnQpEhHl81X4qj7XxvUsmeB1FJKjvXjKejKQ4/ueyTXR0dXsdR8JIBSKCNLd38sA7e1hclMX8sZlexxEJKj0xln///DS2Hm7ggXf2eB1HwkgFIoI89tF+qpva+d6l472OInJSl08bwedmjOL/f2sX2ysavI4jYRLWJUel7xrbOvk/7+7h/AnZuvYgA8JPr5nKh7ur+MGyjTz3zUXE9NNcYU+sOhDy17x5fkHIX3Mw0BlEhPjDB6XUNnfwvUt09iADQ0aSv6lpc3kD96pX06CkAhEBjjS0cv87e7hsynBmaUEgGUCumD6SG+fmc/87e3hruybzG2xUICLAL1/dQWeX45+vmux1FJHTds81U5kyMpXvPLWB3UcbvY4jIaQC4bENB+t4dl0ZX1s8htGZSV7HETlt8TE+HvzSHOKio7j90TXUNLV7HUlCRAXCQ845fvrXLWQlx3HnRUVexxE5Y/kZiTz05WIq6lu57ZHVHGvt8DqShIAKhIee31DO+gN1/PDyiSTHqUOZDGyzC4bxwK2z2Xa4ga/+fo2KxCCgAuGR2qZ2/v3FbczIS2Pp7Dyv44iExEWThvObm2ax4WAdN/1upSb1G+BUIDzysxe3Ut/Swc+vO4eoKPM6jkjIXDl9JL/7cjG7jjSy5L4P2HZYA+kGKhUID7y6uYLn1pfzzQuLmDwy1es4IiF34aQc/vyNhXR2d3Pt/R/wxKoDWq50AFKB6GeH61u46y+bmJ6bxp0X6sK0DF4z8tP5652LKR6dwY+f+5jbfr+GfVVNXseS06AC0Y86urr5zpMbaOvo5tc3ziQ2Wj9+GdxyUuP549fm8dNrprJufy2X3vsu//L8ZsrrWryOJn2grjP96D9e3sbqfTX87xtmMjY72es4Iv0iKsq47dxCrpg2gl+v2MWTqw/w+Kr9XDx5OJ+fmcsFE7PPqhdfV7ejrrmd2uYOapvbqW1up665g7rmdprau2jt8N+6u8HMf4uP8ZEaH0NKfDSZSbHERUcxNTeVouxkovtpTqmBwAZLu2BxcbErKSnxOsYJPbHqAD9+7mO+tmgMd39uSlheXyTSBJsEr7yuhT+t3M+ykjKqGtuIMpg4IpXi0cOYMDyZnNR4hqfGkxTrA8DhX0jr+If/q5uPUNPUTk1TGzVN7dS3dNDd42PMgLTEGNITYkmO8xEf47/5ogznHN0OWjq6ONbaQUNLJ9VNbXR0+V8gJS6ac4syOX9CNhdOzGFUekI//JS8ZWZrnXPFwfbpDKIfvLn1CD95/mMunJjNj66c5HUcEU/lpifwT5dP4geXTWR1aQ0r91az7kAtz60vp7Gts0+vkRjrIzMplvyMRGYmxZKRFMuwRP8tNSEG32n0DOx2jvljMthyqIFVpdW8t7OK17b455UqHj2Ma2aO4qrpI8lMjjujf+9ApgIRZm9vP8o3H1/H9Nw07rt5dr9NiSwS6XxRxsJxmSwc518cq6vbUd3UxtGGNo40tNLS0fX3Y+OjfQxLimVYYgzv7KgkPsYXshxRZowfnsL44Sl8flYuzjn2VDbx2pYKlm84xN0vbOHfXtzKZVNHcMu8AhaOy8RsaHRNV4EIo5c2HeZ7T29g4ogUHv3aPJI0WlrkhHxRRk5KPDkp8UzLTTvhcSv31oQ1h5lRlJNMUU4R37qwiB0Vx1hWcpBn1pXx0qbDjMlK4qZ5+Sydk09GUmxYs3hNf86GgXOO+9/ZzbeeWMc5eWn86fb5pCcO7l8kkcFq4ogUfnL1FFb+6GLuvWEGWcmx/MfL21nwHyv49pPr+XBP1aAd46E/aUOsurGNf3p2E29uO8rV54zkP6+fEdLTYRHxRnyMj2tn5XHtrDx2HjnGE6sO8Jd1ZSzfeIjCzERumFvA0jl5ZKcMnmsV6sUUIt3djuc3lPNvL26lsa2TH185ma+cW9hvbZXqxSRy5s50ydHWji5e2XyYJ1cfZHVpDdFRxiWTh3PDvHwWF2UNiGuO6sUURp1d3by57Sj3v7ObTWX1zMxP55dLz2HC8BSvo4lImPU8q9hT2cjTaw7yzNoyXt1SQVpCDJdMHs4V00aweHzWgGxJUIE4Q+V1LbywoZzHVx6gvK6F3PQEfvXFGXx+Zq4m3xMZgsZlJ/PjKyfzg8sm8u7OSl7ZfJjXt1bw7LoykuOiWVyUxblFmZw7LpNx2ckDoidUWAuEmV0O/BrwAf/lnPt5r/1xwB+BOUA1cINzbl9g34+A24Eu4NvOudfCmfVknHNUNLSypbyBNftreGd7JTuOHANg4dhM/uXqKVwyOUcjMEWE2OgoLp0ynEunDKe9s5sP91Tx6uYK/rarile3VAAwLDGG6XnpnJObxqSRKRRmJlGYlRRx68KELY2Z+YDfApcCZcAaM1vunNva47DbgVrnXJGZ3Qj8ArjBzKYANwJTgVHAm2Y2wTnXRYi1dnSxv7qZ+paOv98aWjqoamyjvK6F8toWSquaqA4soxgdZcwbk8E/z5nMxZNzNGWGiJxQbHQUn5mYw2cm5uCc42BNCx/uqWL9gTo2ldfzwLt76OoxDDwrOY7CzERyUuPITIojIymWrORY0hNjSYz1kRDrIyHGR2JsNImxPuJioojz+b+GowkrnOVqHrDbObcXwMyeApYAPQvEEuCewP1ngPvMf961BHjKOdcGlJrZ7sDrfRTqkNsON3Dt/R9+ant0lDEyPZ7c9AQumTycqbmpTBmZyuSRqRrPICKnzcwoyEykILOAG+f5L4q3dnSxt7KJfdX+2/6qZvZVN7Gj4hjVTdXUNfdtVb6rzhnJb2+eHfLM4fykywUO9nhcBsw/0THOuU4zqwcyA9tX9npubu9vYGZ3AHcEHjaa2Y7QRPfbA1lAVShfM0yUM3QGQkZQzpC6ZWDkPGHG+4H7bznj1x19oh0D+k9h59xDwEPhen0zKzlR969IopyhMxAygnKG2kDI6UXGcF5VLQfyezzOC2wLeoyZRQNp+C9W9+W5IiISRuEsEGuA8WY2xsxi8V90Xt7rmOXAbYH7S4G3nH/k3nLgRjOLM7MxwHhgdRiziohIL2FrYgpcU7gTeA1/N9dHnHNbzOxnQIlzbjnwMPBY4CJ0Df4iQuC4P+O/oN0JfCscPZj6IGzNVyGmnKEzEDKCcobaQMjZ7xkHzVQbIiISWhrZJSIiQalAiIhIUCoQJ2Bml5vZDjPbbWZ3eZ3nODN7xMyOmtnmHtsyzOwNM9sV+DrM44z5Zva2mW01sy1m9p0IzRlvZqvNbGMg508D28eY2arAe/90oJOFp8zMZ2brzezFCM64z8w+NrMNZlYS2BZR73kgU7qZPWNm281sm5ktjLScZjYx8HM8fmsws+/2d04ViCB6TBNyBTAFuCkw/Uck+ANwea9tdwErnHPjgRWBx17qBP6Hc24KsAD4VuDnF2k524CLnHMzgJnA5Wa2AP+UL/c654qAWvxTwnjtO8C2Ho8jMSPAhc65mT3660faew7++eFedc5NAmbg/7lGVE7n3I7Az3Em/rnqmoHn6O+czjndet2AhcBrPR7/CPiR17l65CkENvd4vAMYGbg/EtjhdcZeeV/APydXxOYEEoF1+Ef7VwHRwX4XPMqWF/gwuAh4EbBIyxjIsQ/I6rUtot5z/GOtSgl00InUnL2yXQZ84EVOnUEEF2yakE9N9RFBhjvnDgfuVwDDvQzTk5kVArOAVURgzkDTzQbgKPAGsAeoc851Bg6JhPf+fwM/BLoDjzOJvIwADnjdzNYGpsGByHvPxwCVwO8DTXb/ZWZJRF7Onm4Engzc79ecKhCDjPP/aRERfZfNLBl4Fviuc66h575Iyemc63L+0/g8/BNCTvI20SeZ2dXAUefcWq+z9MFi59xs/E2z3zKz83vujJD3PBqYDTzgnJsFNNGrmSZCcgIQuLZ0DbCs977+yKkCEdxAm+rjiJmNBAh8PepxHswsBn9xeNw595fA5ojLeZxzrg54G39zTXpg6hfw/r1fBFxjZvuAp/A3M/2ayMoIgHOuPPD1KP728nlE3nteBpQ551YFHj+Dv2BEWs7jrgDWOeeOBB73a04ViOD6Mk1IJOk5Zclt+Nv8PWNmhn+U/Dbn3K967Iq0nNlmlh64n4D/Osk2/IViaeAwT3M6537knMtzzhXi/z18yzl3CxGUEcDMksws5fh9/O3mm4mw99w5VwEcNLOJgU0X45+xIaJy9nAT/928BP2d0+sLMJF6A64EduJvk/5nr/P0yPUkcBjowP/X0O3426RXALuAN4EMjzMuxn/quwnYELhdGYE5zwHWB3JuBu4ObB+Lf+6v3fhP7eO8ft8DuT4DvBiJGQN5NgZuW47/n4m09zyQaSZQEnjfnweGRWjOJPyTl6b12NavOTXVhoiIBKUmJhERCUoFQkREglKBEBGRoFQgREQkKBUIEREJSgVCJAgzawzz63/XzBJP9f3M7PuBWXE3mdkKMxsdzlwiPalAiHjju/gnCDyV9UCxc+4c/KN+fxnOUCI9qUCI9JGZjTOzVwOT0f3NzCYFtv/BzH5jZh+a2V4zWxrYHmVm9wfWHXjDzF42s6Vm9m1gFPC2mb3d4/X/V2BtipVmNhzAOfe2c645cMhK/NNqiPQLFQiRvnsI+Efn3BzgB8D9PfaNxD+C/Grg54FtX8A/NfsU4Ev453nCOfcb4BD+tRMuDBybBKx0/rUp3gP+Icj3vx14JYT/HpGTij71ISISmJn2XGCZf6opAOJ6HPK8c64b2Hr8r3/8BWNZYHtFz7OFINrxr/UAsBb/vFA9v/+tQDFwwVn9Q0ROgwqESN9E4V+DYeYJ9rf1uG8nOOZkOtx/z3vTRY//m2Z2CfDPwAXOubZgTxYJBzUxifSB869nUWpm14N/xlozm3GKp30AXBe4FjEc/2R7xx0DUk71fc1sFvAgcI3zT6Mt0m9UIESCSzSzsh637wO3ALeb2fEZS5ec4jWexT/j7lbgT/iXNK0P7HsIePUUzU4A/x+QjL9pa4OZRfK08zLIaDZXkTAys2TnXKOZZeKfnnuR869JIBLxdA1CJLxeDCxKFAv8m4qDDCQ6gxARkaB0DUJERIJSgRARkaBUIEREJCgVCBERCUoFQkREgvq/0CFn5iPUs3kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : Length2\n",
    "sbn.distplot(fish_new['Length2'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "essential-showcase",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Length3', ylabel='Density'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : Length3\n",
    "sbn.distplot(fish_new['Length3'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "direct-artist",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Height', ylabel='Density'>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : Height\n",
    "sbn.distplot(fish_new['Height'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "armed-miami",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Width', ylabel='Density'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : Width\n",
    "sbn.distplot(fish_new['Width'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "basic-sussex",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1e02feff550>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1080x1080 with 42 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : New Fish Dataset\n",
    "sbn.pairplot(fish_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "cellular-stanford",
   "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>Weight</th>\n",
       "      <th>Length1</th>\n",
       "      <th>Length2</th>\n",
       "      <th>Length3</th>\n",
       "      <th>Height</th>\n",
       "      <th>Width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Weight</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.915581</td>\n",
       "      <td>0.918322</td>\n",
       "      <td>0.922943</td>\n",
       "      <td>0.728389</td>\n",
       "      <td>0.889215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Length1</th>\n",
       "      <td>0.915581</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.999500</td>\n",
       "      <td>0.991842</td>\n",
       "      <td>0.627461</td>\n",
       "      <td>0.868297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Length2</th>\n",
       "      <td>0.918322</td>\n",
       "      <td>0.999500</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.993988</td>\n",
       "      <td>0.642989</td>\n",
       "      <td>0.875030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Length3</th>\n",
       "      <td>0.922943</td>\n",
       "      <td>0.991842</td>\n",
       "      <td>0.993988</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.706586</td>\n",
       "      <td>0.879987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Height</th>\n",
       "      <td>0.728389</td>\n",
       "      <td>0.627461</td>\n",
       "      <td>0.642989</td>\n",
       "      <td>0.706586</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.792881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Width</th>\n",
       "      <td>0.889215</td>\n",
       "      <td>0.868297</td>\n",
       "      <td>0.875030</td>\n",
       "      <td>0.879987</td>\n",
       "      <td>0.792881</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Weight   Length1   Length2   Length3    Height     Width\n",
       "Weight   1.000000  0.915581  0.918322  0.922943  0.728389  0.889215\n",
       "Length1  0.915581  1.000000  0.999500  0.991842  0.627461  0.868297\n",
       "Length2  0.918322  0.999500  1.000000  0.993988  0.642989  0.875030\n",
       "Length3  0.922943  0.991842  0.993988  1.000000  0.706586  0.879987\n",
       "Height   0.728389  0.627461  0.642989  0.706586  1.000000  0.792881\n",
       "Width    0.889215  0.868297  0.875030  0.879987  0.792881  1.000000"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# New Fish Dataset Correlation\n",
    "fish_new.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "champion-prime",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# New Fish Dataset Correlation Heatmap\n",
    "sbn.heatmap(fish_new.corr())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "altered-individual",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Task 2 Conclusion :\n",
    "# 1. There is a strong correlation between Length1 - Length2 - Length3 independent variables.\n",
    "# 2. Keeping [1] in mind, we will use only one Length , Height and Width for determination of Weight."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "identified-inspection",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating new dataset keeping Task 2 Conclusion in mind\n",
    "fish_data = fish_new[['Weight','Length1','Height','Width']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "tender-rhythm",
   "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>Weight</th>\n",
       "      <th>Length1</th>\n",
       "      <th>Height</th>\n",
       "      <th>Width</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>242.0</td>\n",
       "      <td>23.2</td>\n",
       "      <td>11.5200</td>\n",
       "      <td>4.0200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>290.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>12.4800</td>\n",
       "      <td>4.3056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>340.0</td>\n",
       "      <td>23.9</td>\n",
       "      <td>12.3778</td>\n",
       "      <td>4.6961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>363.0</td>\n",
       "      <td>26.3</td>\n",
       "      <td>12.7300</td>\n",
       "      <td>4.4555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>430.0</td>\n",
       "      <td>26.5</td>\n",
       "      <td>12.4440</td>\n",
       "      <td>5.1340</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Weight  Length1   Height   Width\n",
       "0   242.0     23.2  11.5200  4.0200\n",
       "1   290.0     24.0  12.4800  4.3056\n",
       "2   340.0     23.9  12.3778  4.6961\n",
       "3   363.0     26.3  12.7300  4.4555\n",
       "4   430.0     26.5  12.4440  5.1340"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test\n",
    "fish_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "fourth-sending",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAD4CAYAAAD7CAEUAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAAAc2UlEQVR4nO3deZhcdZ3v8fenq7uTTsgCSZNAAiSQAIZNIAKKLAMSQYS4oAZxQAdFRcaFce5FHbgOeu8dnEeccWRUEDREGEAcICKKRDYVg+lAMAsEOhskJNABsi+9feePOp1UOtXpPkmfqkryeT1PPXXqd37n1LdOpfLps9SvFBGYmZn1VFW5CzAzs92Lg8PMzFJxcJiZWSoODjMzS8XBYWZmqVSXu4BSGDp0aIwaNarcZZiZ7VZmzpy5MiLqO7fvFcExatQoGhoayl2GmdluRdKSYu0+VGVmZqk4OMzMLBUHh5mZpeLgMDOzVBwcZmaWioPDzMxScXCYmVkqDg4zM0vFwWFmZqnsFd8c313d+fTL27V9/OSDy1CJmdlW3uMwM7NUHBxmZpaKg8PMzFJxcJiZWSoODjMzS8XBYWZmqTg4zMwsFQeHmZml4uAwM7NUHBxmZpaKg8PMzFJxcJiZWSoODjMzS8XBYWZmqTg4zMwsFQeHmZml4uAwM7NUHBxmZpaKg8PMzFJxcJiZWSqZBoekcyXNl9Qo6Zoi8/tIujuZ/7SkUUn7OZJmSpqd3J9VsMyJSXujpO9LUpavwczMtpVZcEjKATcB5wHjgIsljevU7XLgrYgYA3wPuCFpXwlcEBHHAJcBUwqW+SHwGWBscjs3q9dgZmbby3KP4ySgMSIWRkQzcBcwsVOficDkZPpe4GxJiohnI+LVpH0uUJfsnRwADIyI6RERwO3ABzJ8DWZm1kmWwTECeKXg8dKkrWifiGgFVgNDOvX5MPBMRGxO+i/tZp0ASLpCUoOkhqampp1+EWZmtq2KPjku6Sjyh68+m3bZiLg5IsZHxPj6+vreL87MbC+VZXAsAw4qeDwyaSvaR1I1MAh4I3k8ErgPuDQiFhT0H9nNOs3MLENZBscMYKyk0ZJqgUnA1E59ppI/+Q1wEfBoRISkwcCvgWsi4k8dnSNiObBG0inJ1VSXAg9k+BrMzKyTzIIjOWdxFfAw8DxwT0TMlXS9pAuTbrcCQyQ1AlcDHZfsXgWMAa6TNCu57Z/MuxL4CdAILAB+k9VrMDOz7VVnufKIeAh4qFPbdQXTm4CPFFnu28C3u1hnA3B071ZqZmY9VdEnx83MrPI4OMzMLBUHh5mZpeLgMDOzVBwcZmaWioPDzMxScXCYmVkqDg4zM0vFwWFmZqk4OMzMLBUHh5mZpeLgMDOzVBwcZmaWioPDzMxScXCYmVkqDg4zM0vFwWFmZqk4OMzMLBUHh5mZpeLgMDOzVBwcZmaWioPDzMxScXCYmVkqDg4zM0vFwWFmZqk4OMzMLBUHh5mZpeLgMDOzVBwcZmaWioPDzMxScXCYmVkqDg4zM0vFwWFmZqk4OMzMLBUHh5mZpeLgMDOzVDINDknnSpovqVHSNUXm95F0dzL/aUmjkvYhkh6TtE7SDzot83iyzlnJbf8sX4OZmW2rOqsVS8oBNwHnAEuBGZKmRsS8gm6XA29FxBhJk4AbgI8Bm4BrgaOTW2eXRERDVrWbmVnXstzjOAlojIiFEdEM3AVM7NRnIjA5mb4XOFuSImJ9RPyRfICYmVkFyTI4RgCvFDxemrQV7RMRrcBqYEgP1v3T5DDVtZLUG8WamVnP7I4nxy+JiGOA05Lb3xbrJOkKSQ2SGpqamkpaoJnZnizL4FgGHFTweGTSVrSPpGpgEPDGjlYaEcuS+7XAneQPiRXrd3NEjI+I8fX19Tv1AszMbHtZBscMYKyk0ZJqgUnA1E59pgKXJdMXAY9GRHS1QknVkoYm0zXA+4E5vV65mZl1KbOrqiKiVdJVwMNADrgtIuZKuh5oiIipwK3AFEmNwJvkwwUASYuBgUCtpA8AE4AlwMNJaOSAacAtWb0GMzPbXmbBARARDwEPdWq7rmB6E/CRLpYd1cVqT+yt+szMLL3d8eS4mZmVkYPDzMxScXCYmVkqDg4zM0vFwWFmZqk4OMzMLBUHh5mZpdKj4JD035LOl+SgMTPby/U0CP4T+DjwkqR/kXREhjWZmVkF61FwRMS0iLgEOAFYDEyT9JSkTyXDf5iZ2V6ix4eeJA0BPgl8GngW+HfyQfJIJpWZmVlF6tFYVZLuA44ApgAXRMTyZNbdkvwTrmZme5GeDnJ4SzJg4RaS+kTE5ogYn0FdZmZWoXp6qOrbRdr+3JuFmJnZ7mGHexyShpP/XfA6SccDHb/vPRDol3FtZmZWgbo7VPVe8ifERwI3FrSvBb6eUU1mZlbBdhgcETEZmCzpwxHxyxLVZGZmFay7Q1WfiIifA6MkXd15fkTcWGQxMzPbg3V3qKp/cr9P1oWYmdnuobtDVT9O7v+5NOWYmVml6+kgh9+RNFBSjaTfS2qS9ImsizMzs8rT0+9xTIiINcD7yY9VNQb4x6yKMjOzytXT4Og4pHU+8IuIWJ1RPWZmVuF6OuTIg5JeADYCn5dUD2zKriwzM6tUPR1W/RrgXcD4iGgB1gMTsyzMzMwqU0/3OACOJP99jsJlbu/leszMrML1dFj1KcBhwCygLWkOHBxmZnudnu5xjAfGRURkWYyZmVW+nl5VNQcYnmUhZma2e+jpHsdQYJ6kvwCbOxoj4sJMqjIzs4rV0+D4ZpZFmJnZ7qNHwRERT0g6BBgbEdMk9QNy2ZZmZmaVqKdjVX0GuBf4cdI0Arg/o5rMzKyC9fTk+BeAU4E1ABHxErB/VkWZmVnl6mlwbI6I5o4HyZcAfWmumdleqKfB8YSkrwN1ks4BfgH8KruyzMysUvU0OK4BmoDZwGeBh4B/yqooMzOrXD0d5LCd/MnwKyPiooi4pSffIpd0rqT5kholXVNkfh9Jdyfzn5Y0KmkfIukxSesk/aDTMidKmp0s831J6slrMDOz3rHD4FDeNyWtBOYD85Nf/7uuuxVLygE3AecB44CLJY3r1O1y4K2IGAN8D7ghad8EXAt8tciqfwh8Bhib3M7trhYzM+s93e1xfIX81VTviIj9ImI/4GTgVElf6WbZk4DGiFiYnFi/i+2HYp8ITE6m7wXOlqSIWB8Rf6TTb35IOgAYGBHTkz2e24EPdFOHmZn1ou6C42+BiyNiUUdDRCwEPgFc2s2yI4BXCh4vTdqK9omIVmA1MKSbdS7tZp0ASLpCUoOkhqampm5KNTOznuouOGoiYmXnxohoAmqyKal3RMTNETE+IsbX19eXuxwzsz1Gd8HRvJPzAJYBBxU8Hpm0Fe2TfDdkEPBGN+sc2c06zcwsQ90Fx3GS1hS5rQWO6WbZGcBYSaMl1QKTgKmd+kwFLkumLwIe3dHVWhGxHFgj6ZTkaqpLgQe6qcPMzHrRDgc5jIidHsgwIlolXQU8TH5AxNsiYq6k64GGiJgK3ApMkdQIvEk+XACQtBgYCNRK+gAwISLmAVcCPwPqgN8kNzMzK5E0vzmeWkQ8RP7LgoVt1xVMbwI+0sWyo7pobwCO7r0qzcwsjZ5+c9zMzAxwcJiZWUoODjMzS8XBYWZmqTg4zMwsFQeHmZml4uAwM7NUHBxmZpaKg8PMzFJxcJiZWSoODjMzS8XBYWZmqTg4zMwsFQeHmZml4uAwM7NUHBxmZpaKg8PMzFJxcJiZWSoODjMzS8XBYWZmqTg4zMwsFQeHmZml4uAwM7NUHBxmZpaKg8PMzFJxcJiZWSoODjMzS8XBYWZmqTg4zMwsFQeHmZml4uAwM7NUHBxmZpaKg8PMzFJxcJiZWSoODjMzS8XBYWZmqTg4zMwslUyDQ9K5kuZLapR0TZH5fSTdncx/WtKognlfS9rnS3pvQftiSbMlzZLUkGX9Zma2veqsViwpB9wEnAMsBWZImhoR8wq6XQ68FRFjJE0CbgA+JmkcMAk4CjgQmCbp8IhoS5b7m4hYmVXtZmbWtSz3OE4CGiNiYUQ0A3cBEzv1mQhMTqbvBc6WpKT9rojYHBGLgMZkfWZmVmZZBscI4JWCx0uTtqJ9IqIVWA0M6WbZAH4naaakK7p6cklXSGqQ1NDU1LRLL8TMzLbaHU+OvzsiTgDOA74g6fRinSLi5ogYHxHj6+vrS1thL4oINre0dd/RzKxEMjvHASwDDip4PDJpK9ZnqaRqYBDwxo6WjYiO+9cl3Uf+ENaTWbyAclq1oZl7Gl5h3vI1NLe2c/B+/TjziN03AM1sz5HlHscMYKyk0ZJqyZ/sntqpz1TgsmT6IuDRiIikfVJy1dVoYCzwF0n9JQ0AkNQfmADMyfA1lMWCpnWc+29/4K9LV3HcyEGcdeT+rNvcyu1/XsKUPy8ud3lmtpfLbI8jIlolXQU8DOSA2yJirqTrgYaImArcCkyR1Ai8ST5cSPrdA8wDWoEvRESbpGHAffnz51QDd0bEb7N6DeWwemMLn5ncQEtbO58/Ywwj9q0D4IzD67nrLy9z7QNzqaut5qITR5a5UjPbWyn/B/6ebfz48dHQsHt85eNzU2Yy7fnXuOPTJ7Ogaf0289rag1/PfpXZS1fz6y+exqih/ctUpZntDSTNjIjxndt3x5Pje6zHXnid385dwdUTDufkQ4dsNz9XJW786NvJVYmv3DOL9vY9P/TNrPI4OCrE5tY2/vlXczm0vj+ffvehXfY7cHAd111wFM++vIoHnut8rYGZWfYcHBXizqdfZvEbG/jmBUdRW73jt+VDx4/gmBGD+M5v57Ox2ZfqmllpOTgqwObWNn78xEJOGr0fpx/e/SW3VVXin85/G8tXb2Kyr7IysxJzcFSAXzQsZcWaTXzxrLE9XubkQ4fw7jFDufWPi9jkLwiaWQk5OMqsrT348ZMLOP7gwZw6ZvsT4jty5ZmH0bR2M798ZmlG1ZmZbc/BUWbTnn+NV97cyBWnHUry/ZQee+dhQzhu5CB+/MRCWtvaM6rQzGxbDo4y++mfFjFicB3njBuWellJfP7MMbz85gYemrMig+rMzLbn4Cijea+uYfrCN7n0nYdQndu5t2LCuGEcVt+fHz6+gL3hy5xmVn4OjjKaMn0JfWuqmPSOg3d6HVVV4nNnHMbzy9fw+HwPH29m2XNwlMnaTS08MGsZFxx7IIP61ezSuia+fQQHDOrLzU8u7KXqzMy65uAok/tnvcqG5jYuOeWQXV5XbXUVn3zXKP688A3mLFvdC9WZmXXNwVEGEcEd05dw1IEDOW7koF5Z56STDqZ/bY5b/7ioV9ZnZtYVB0cZPPPyKl5YsZZPnHJI6ktwuzKoroaPvuMgfvXcqyxfvbFX1mlmVoyDowzumL6EffpUc+FxB/bqev/u1NG0R/Czpxb36nrNzAo5OErsrfXNPDh7OR88fgT9+/Tu72gdtF8/zj16OHc+/TLrN7f26rrNzDo4OErsFzNfobm1nUtO2flLcHfk06cdytpNrdw945VM1m9m5uAoobb2YPJTSzh59H4cOXxgJs9xwsH78o5R+/KTPyykudXDkJhZ78vsN8dte9Oef41lqzZy7fvfttPruPPpl7dr+/jJ2+69XPk3Y/jUT2dw/7PL+Og7Dtrp5zIzK8Z7HCXUMS7Ve96WflyqNM48vJ6jDhzID59YQJt/XtbMepmDo0SeX77r41L1lCT+/qwxLFq5nvue9c/LmlnvcnCUyM/+tJi+NVV8rESHjiaMG87RIwbyb9Ne9LkOM+tVDo4SeHN9M/fPWsYHjx/J4H61JXnOqirx1QlHsPStjdw9Y/vzImZmO8vBUQJ3Pr2Eza3tfOrUUSV93jMOr+fk0ftx4yMvsnpDS0mf28z2XA6OjK3b3MpP/riIs47cn8OHDSjpc0vi/1xwFKs3tnDjI/NL+txmtudycGTs59OXsGpDC39/1piyPP+4AwfyiVMOYcr0Jfx16aqy1GBmexYHR4bWbW7llicXcvrh9Rx/8L5lq+MfJhzB/gP6cvU9z7Gppa1sdZjZnsHBkaEfPb6AN9Y3c/U5h5e1jkF1Ndxw0bE0vr6O7/zWh6zMbNc4ODLy6qqN3PKHhUx8+4G8/aDB5S6HMw6v55PvGsVtf1rEA7P83Q4z23kOjox868F5BPCP7z2i3KVs8fX3vY2TRu3H//7lX5m55M1yl2NmuykHRwYemr2c38xZwZffM5aR+/Yrdzlb1FZXcdMlJ3DAoDo+edsMnntlVblLMrPdkIOjl72+ZhPXPTCHY0YM4orTDi13OdupH9CHOz59MoP61XDxLdOZNu+1cpdkZrsZB0cvam5t5/N3PMP6zW1896PHZT4m1c46cHAdv/z8uzisfh8+M6WB//fQ877aysx6zMOq95L29uDr981m5pK3+MHHjy/5l/26U2w49ns++06uf3AeNz+5kIfnruAfJhzB+cccQK6qd34H3cz2TJX5J/Fupq09+Mb9c7h35lK+/J6xvP/Y3v0t8azU1eb4/x86himXn0RdTY4v/teznPGvj/H937/EnGWrifCQ7Ga2Pe9x7KLVG1r40t3P8vj8Jq488zC+dPbYcpdUdO9iR04bW8+vvziUh+euYPJTi7nxkRe58ZEX2X9AH04dM5Qjhw/giOEDGLP/Pgwb2JeaCj0EZ2al4eDYSe3twa9nL+dbD87jrQ3N/N8PHs0lJx9SllrSBsWOlrv7s++kae1mnnixicdeeJ2nFqzc5jc9JBjSvw/DBvZh+MC+DNmnlsH9ahlUV8NLr62jrjZHv+R28UkHM7hfDXU1OSQf/jLbU2QaHJLOBf4dyAE/iYh/6TS/D3A7cCLwBvCxiFiczPsacDnQBnwxIh7uyTqztnLdZn4zZwW3P7WYl15fx9EjBvKTy8Zz7MjBpSwjU/UD+nDRiSO56MSRAKza0MwLK9ayaOV6VqzexGtrNvHMy28x99U1bGhuZUNzG61FfmnwPx5tBKA2V8XgfjX5W10tg/rVsE+favrV5ujfcV9bTV1tjpqcqFL+lqsSElvOuURAx7N0HEb7U+PKLfMA3nnYkO36BWxpCGJL3619ttac9N6uT3dmLHqTKonqnKiuEme/bRh9qqvyt5ocfaqr6Jvc96muojpXRU1OVFfl73clWCNiy2tuT6bbt7QF7QWPAe57Zhm5Km1zLqvzzw+b7YiyOo4tKQe8CJwDLAVmABdHxLyCPlcCx0bE5yRNAj4YER+TNA74L+Ak4EBgGtAxbscO11nM+PHjo6GhIfVrmLNsNYtWrmfJG+tZ8sYGZi9bzfzX1hIBRw4fwBWnH8qFxx2Y2dVTO7snUQ4tbe1saG5jY3PbljDZ2NLxON+2saWNAX2rWbWhZUvb+s35fnu7XFU+cGpyVVt+7rcj5ALISVtCgCQI2pNQ3NmPsIDqXD5A9ulTTW0uH3J9a3L0ramib3X+vq42R9/qHH1qctR1zCuY3tqe9K/J0ac6R1VV/nUV/iGQ09Y/Brb8YdDxRwJdhGeR5q5ytlhzsVDuKqaLrXdLEAPRvnXbt8fW96jj8f3PLEvek63vzfnHDs/3TfpJJNskX1su2T5S/nd0qpL5W/sl261q63Kd53esq7dJmhkR4zu3Z7nHcRLQGBELkwLuAiYChf/JTwS+mUzfC/xA+Vc/EbgrIjYDiyQ1JuujB+vsNV+661kWNK0H8n+FHzl8AOcfcwDnHDWMI4YN8OGXAjW5KgbVVTGorib1su0RNLe209zavu1fzGz7lzIkH3h1TKvT44J+Be9NR5+u5ndettj6evY68hdKtLS109oetLa109IWtLa301pw39LWTlt7/j+atoj8dHvQFlvvRf4/BhXUWvi48DV1PFbSWNXxWgvaO/oF+cOsre35GtvaIl9re2ytva2dtZtaqe4nmta1sKmlnU0tbWxqaWftphZa2trxT9n33PemvViS5+kcSB0B88y159C3Jterz5VlcIwAXil4vBQ4uas+EdEqaTUwJGmf3mnZEcl0d+sEQNIVwBXJw3WSuhrdbyiwcoevBFgCNAA/765j7+pRbWVQqXWBa9sZlVoXVG5tlVoXdKqt7lu7tK6iJ2732JPjEXEzcHN3/SQ1FNsVqwSVWlul1gWubWdUal1QubVVal1QmtqyvK5yGXBQweORSVvRPpKqgUHkT5J3tWxP1mlmZhnKMjhmAGMljZZUC0wCpnbqMxW4LJm+CHg08mfrpwKTJPWRNBoYC/ylh+s0M7MMZXaoKjlncRXwMPlLZ2+LiLmSrgcaImIqcCswJTn5/Sb5ICDpdw/5k96twBciog2g2Dp3sdRuD2eVUaXWVql1gWvbGZVaF1RubZVaF5SgtswuxzUzsz2Tx44wM7NUHBxmZpbKXhUckv5V0guS/irpPkmDk/ZRkjZKmpXcflSwzImSZktqlPR9leBbf5LOlTQ/ec5rsn6+Is9/kKTHJM2TNFfSl5L2b0paVrCd3lewzNeSeudLem+GtS1O3o9ZkhqStv0kPSLppeR+36RdyXvWmLznJ2RY1xEF22WWpDWSvlyubSbpNkmvS5pT0JZ6O0m6LOn/kqTLij1XL9RVEZ/LLmpL/f719ue3i7ruLqhpsaRZSXtptll+nJu94wZMAKqT6RuAG5LpUcCcLpb5C3AK+S/f/gY4L+Mac8AC4FCgFngOGFfi7XQAcEIyPYD8MC/jyH/L/6tF+o9L6uwDjE7qz2VU22JgaKe27wDXJNPXFLyv70veMyXv4dMl2n45YAX5L0+VZZsBpwMnFP67TrudgP2Ahcn9vsn0vhnUVRGfyy5qS/X+ZfH5LVZXp/nfBa4r5Tbbq/Y4IuJ3EdGaPJxO/nsgXZJ0ADAwIqZHfsvfDnwg2yq3DtUSEc1Ax7AqJRMRyyPimWR6LfA8W7+5X8yWIWIiYhFQOERMKUwEJifTk9n6Hk0Ebo+86cDg5D3N2tnAgohYsoM+mW6ziHiS/JWKnZ8zzXZ6L/BIRLwZEW8BjwDn9nZdlfK57GKbdaWr96/XP787qivZa/go+bH9utTb22yvCo5O/o586nYYLelZSU9IOi1pG0F+WJMOhUOfZKXYUC1ZP2eXJI0CjgeeTpquSg4p3NZxqIPS1hzA7yTNVH5YGYBhEbE8mV4BDCtDXYUmse0HudzbrEPa7VSOGivxc5nm/Sv1NjsNeC0iXipoy3yb7XHBIWmapDlFbhML+nyD/PdD7kialgMHR8TxwNXAnZIGlr76yiJpH+CXwJcjYg3wQ+Aw4O3kt9l3y1DWuyPiBOA84AuSTi+cmfw1VbZrzJX/YuqFwC+SpkrYZtsp93YqpkI/lxX5/hW4mG3/SCnJNtvjxqqKiPfsaL6kTwLvB85OPjxEfhTezcn0TEkLyA/jvoxtd5tLMcRJRQyrIqmGfGjcERH/DRARrxXMvwV4MHlYspojYlly/7qk+8gfGnhN0gERsTzZJX+91HUVOA94pmNbVcI2K5B2Oy0DzuzU/ngWhVXq53In37+SvK/KD9P0IfK/Z9RRb0m22R63x7Ejyv8I1P8CLoyIDQXt9cr/fgiSDiU/xMnCZLd+jaRTkmOJlwIPZFxm2YdVSV7rrcDzEXFjQXvh+YEPAh1XeXQ1RExv19Vf0oCOafInVeew7dA1l7H1PZoKXKq8U4DVBYdqsrLNX4Dl3madpN1ODwMTJO2bHKKZkLT1qkr+XO7E+1fKz+97gBciYsshqJJts10527+73cifwHoFmJXcfpS0fxiYm7Q9A1xQsMx48v9YFgA/IPm2fcZ1vo/8lUwLgG+UYTu9m/xhjL8WbKv3AVOA2Un7VOCAgmW+kdQ7n4yuPCN/pcpzyW1ux7YhPxT/74GXyP/o135Ju4CbkrpmA+Mz3m79yQ/SOaigrSzbjHx4LQdayB/PvnxnthP5cw6Nye1TGdVVEZ/LLmpL/f719ue3WF1J+8+Az3XqW5Jt5iFHzMwslb3qUJWZme06B4eZmaXi4DAzs1QcHGZmloqDw8zMUnFwmJlZKg4OMzNL5X8A6qieCVD/oBAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : New Fish Data\n",
    "sbn.distplot(fish_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "damaged-scheduling",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Instantiating : MinMaxScaler Object\n",
    "mms = MinMaxScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "upset-adrian",
   "metadata": {},
   "outputs": [],
   "source": [
    "fish_data_new = mms.fit_transform(fish_data)\n",
    "fd_new = pd.DataFrame(fish_data_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "purple-hours",
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.150601</td>\n",
       "      <td>0.291485</td>\n",
       "      <td>0.568334</td>\n",
       "      <td>0.418978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.181279</td>\n",
       "      <td>0.308766</td>\n",
       "      <td>0.624055</td>\n",
       "      <td>0.459235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.213236</td>\n",
       "      <td>0.306606</td>\n",
       "      <td>0.618123</td>\n",
       "      <td>0.514279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.227935</td>\n",
       "      <td>0.358448</td>\n",
       "      <td>0.638566</td>\n",
       "      <td>0.480365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.270757</td>\n",
       "      <td>0.362768</td>\n",
       "      <td>0.621966</td>\n",
       "      <td>0.576004</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3\n",
       "0  0.150601  0.291485  0.568334  0.418978\n",
       "1  0.181279  0.308766  0.624055  0.459235\n",
       "2  0.213236  0.306606  0.618123  0.514279\n",
       "3  0.227935  0.358448  0.638566  0.480365\n",
       "4  0.270757  0.362768  0.621966  0.576004"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test\n",
    "fd_new.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "protecting-future",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualization : fd_new\n",
    "sbn.distplot(fd_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "limited-louisiana",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Task 3 : Build a regression model and print regression equation.\n",
    "X = fd_new.iloc[:,1:]\n",
    "Y = fd_new.iloc[:,:1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "editorial-sapphire",
   "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>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.291485</td>\n",
       "      <td>0.568334</td>\n",
       "      <td>0.418978</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.308766</td>\n",
       "      <td>0.624055</td>\n",
       "      <td>0.459235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.306606</td>\n",
       "      <td>0.618123</td>\n",
       "      <td>0.514279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.358448</td>\n",
       "      <td>0.638566</td>\n",
       "      <td>0.480365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.362768</td>\n",
       "      <td>0.621966</td>\n",
       "      <td>0.576004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>0.038752</td>\n",
       "      <td>0.021012</td>\n",
       "      <td>0.048771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>0.043073</td>\n",
       "      <td>0.040723</td>\n",
       "      <td>0.031208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>0.051713</td>\n",
       "      <td>0.031842</td>\n",
       "      <td>0.029347</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>0.075474</td>\n",
       "      <td>0.066424</td>\n",
       "      <td>0.143719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>0.088435</td>\n",
       "      <td>0.069872</td>\n",
       "      <td>0.117219</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            1         2         3\n",
       "0    0.291485  0.568334  0.418978\n",
       "1    0.308766  0.624055  0.459235\n",
       "2    0.306606  0.618123  0.514279\n",
       "3    0.358448  0.638566  0.480365\n",
       "4    0.362768  0.621966  0.576004\n",
       "..        ...       ...       ...\n",
       "154  0.038752  0.021012  0.048771\n",
       "155  0.043073  0.040723  0.031208\n",
       "156  0.051713  0.031842  0.029347\n",
       "157  0.075474  0.066424  0.143719\n",
       "158  0.088435  0.069872  0.117219\n",
       "\n",
       "[159 rows x 3 columns]"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test : X\n",
    "X"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "saved-confirmation",
   "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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.150601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.181279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.213236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.227935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.270757</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>0.003730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>0.004497</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>0.003730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>0.008523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>0.008651</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>159 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0\n",
       "0    0.150601\n",
       "1    0.181279\n",
       "2    0.213236\n",
       "3    0.227935\n",
       "4    0.270757\n",
       "..        ...\n",
       "154  0.003730\n",
       "155  0.004497\n",
       "156  0.003730\n",
       "157  0.008523\n",
       "158  0.008651\n",
       "\n",
       "[159 rows x 1 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test : Y\n",
    "Y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "human-deficit",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Splitting X and Y into testing and training datasets\n",
    "X_train , X_test , Y_train, Y_test = train_test_split(X,Y,test_size=0.2,random_state=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "surrounded-parliament",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(127, 3)\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>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>0.200760</td>\n",
       "      <td>0.395227</td>\n",
       "      <td>0.316700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.243963</td>\n",
       "      <td>0.279860</td>\n",
       "      <td>0.321014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>0.390850</td>\n",
       "      <td>0.341711</td>\n",
       "      <td>0.524921</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>0.334687</td>\n",
       "      <td>0.382771</td>\n",
       "      <td>0.576469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>0.339007</td>\n",
       "      <td>0.308975</td>\n",
       "      <td>0.463380</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            1         2         3\n",
       "66   0.200760  0.395227  0.316700\n",
       "46   0.243963  0.279860  0.321014\n",
       "108  0.390850  0.341711  0.524921\n",
       "102  0.334687  0.382771  0.576469\n",
       "104  0.339007  0.308975  0.463380"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test : X Training\n",
    "print(X_train.shape)\n",
    "X_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "registered-auditor",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(32, 3)\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>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>0.008511</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.343327</td>\n",
       "      <td>0.409180</td>\n",
       "      <td>0.512235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.278524</td>\n",
       "      <td>0.290505</td>\n",
       "      <td>0.439530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>0.222361</td>\n",
       "      <td>0.254321</td>\n",
       "      <td>0.349205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>0.654383</td>\n",
       "      <td>0.295822</td>\n",
       "      <td>0.480858</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            1         2         3\n",
       "147  0.008511  0.000000  0.014208\n",
       "57   0.343327  0.409180  0.512235\n",
       "98   0.278524  0.290505  0.439530\n",
       "88   0.222361  0.254321  0.349205\n",
       "135  0.654383  0.295822  0.480858"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test : X Testing\n",
    "print(X_test.shape)\n",
    "X_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "southern-strap",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(127, 1)\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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>0.085410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.085410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>0.200453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>0.187670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>0.165301</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            0\n",
       "66   0.085410\n",
       "46   0.085410\n",
       "108  0.200453\n",
       "102  0.187670\n",
       "104  0.165301"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test : Y Training\n",
    "print(Y_train.shape)\n",
    "Y_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "desperate-institution",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(32, 1)\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>0</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>0.000406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>0.191505</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>0.116088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>0.079019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>0.321887</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            0\n",
       "147  0.000406\n",
       "57   0.191505\n",
       "98   0.116088\n",
       "88   0.079019\n",
       "135  0.321887"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data Test : Y Testing\n",
    "print(Y_test.shape)\n",
    "Y_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "professional-narrative",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Instantiating : linear Regression Object\n",
    "lr = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "lasting-parcel",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Training Linear Regression Model\n",
    "lr.fit(X_train,Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "friendly-friday",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.13837148],\n",
       "       [ 0.24723871],\n",
       "       [ 0.1716003 ],\n",
       "       [ 0.11058527],\n",
       "       [ 0.41589136],\n",
       "       [ 0.54954486],\n",
       "       [ 0.10622403],\n",
       "       [ 0.71019599],\n",
       "       [ 0.20292531],\n",
       "       [ 0.25220764],\n",
       "       [ 0.14943626],\n",
       "       [ 0.33066177],\n",
       "       [-0.04288331],\n",
       "       [ 0.52192227],\n",
       "       [ 0.13676587],\n",
       "       [-0.06250173],\n",
       "       [ 0.15473324],\n",
       "       [ 0.46731436],\n",
       "       [ 0.41400809],\n",
       "       [ 0.58852434],\n",
       "       [ 0.48541921],\n",
       "       [ 0.35973046],\n",
       "       [-0.10651847],\n",
       "       [ 0.05653468],\n",
       "       [ 0.50838578],\n",
       "       [ 0.28431126],\n",
       "       [ 0.18013141],\n",
       "       [ 0.12676968],\n",
       "       [ 0.12992476],\n",
       "       [ 0.36701009],\n",
       "       [ 0.0201618 ],\n",
       "       [ 0.41092273]])"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Pedicting Y using X test data\n",
    "Y_predicted = lr.predict(X_test)\n",
    "Y_predicted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "assisted-tactics",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Length1 : 0.6231\n",
      "Height  : 0.1599\n",
      "Width   : 0.2241\n"
     ]
    }
   ],
   "source": [
    "# Linear Regression : Coefficients\n",
    "print(\"Length1 : {:.4f}\".format(lr.coef_[0][0]))\n",
    "print(\"Height  : {:.4f}\".format(lr.coef_[0][1]))\n",
    "print(\"Width   : {:.4f}\".format(lr.coef_[0][2]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "alpha-economics",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Intercept : -0.1469\n"
     ]
    }
   ],
   "source": [
    "# Linear Regression : Intercept\n",
    "print(\"Intercept : {:.4f}\".format(lr.intercept_[0]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "living-houston",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Regression Equation\n",
    "# Weight = (0.6231 * Length1) + (0.1599 * Height) + (0.2241 * Width) - 0.1469"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "forty-greensboro",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.08297372357539445"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Task 4 : What is the mean score of the model at 95% confidence interval?\n",
    "rm_sq_err = np.sqrt(metrics.mean_squared_error(Y_test , Y_predicted))\n",
    "rm_sq_err"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "shaped-arctic",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.07579113283250274"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Y_pred_train = lr.predict(X_train)\n",
    "rm_sq_err_train = np.sqrt(metrics.mean_squared_error( Y_train, Y_pred_train))\n",
    "rm_sq_err_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "organic-heather",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8846912042525455"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Task 5 : Compare real and predicted weights and give a conclusion statement based on it?\n",
    "metrics.r2_score(Y_train,Y_pred_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "duplicate-provincial",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8798412920600949"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metrics.r2_score(Y_test,Y_predicted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "distinct-spare",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Task 5 Conclusion : \n",
    "# 1. By comparing the above scores it is certain that the model does generate acceptable results with low error.\n",
    "# 2. To increase the accuracy of regression model more datapoints can be introduced.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "organizational-ownership",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}