Lab Sessional Exam.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd99b03c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#1928152 LAB SESSIONAL EXAM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ef13317f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12\n",
      "98\n",
      "2\n",
      "1345\n",
      "pushed: 12\n",
      "pushed: 98\n",
      "pushed: 2\n",
      "pushed: 1345\n",
      "before stack: ['12', '98', '2', '1345']\n",
      "popped: 1345\n",
      "after stack: ['12', '98', '2']\n"
     ]
    }
   ],
   "source": [
    "#1. Implement Stack in Python.Along with Push and Pop Operations.\n",
    "\n",
    "def crt_stack():\n",
    "    stacp = []\n",
    "    return stacp\n",
    "\n",
    "def check_empty(stack):\n",
    "    return len(stack) == 0\n",
    "\n",
    "def push(stack, item):\n",
    "    stack.append(item)\n",
    "    print(\"pushed: \" + item)\n",
    "\n",
    "def pop(stack):\n",
    "    if (check_empty(stack)):\n",
    "        return \"empty\"\n",
    "    return stack.pop()\n",
    "\n",
    "num = input()\n",
    "num1 = input()\n",
    "num2 = input()\n",
    "num3 = input()\n",
    "\n",
    "stack = crt_stack()\n",
    "push(stack, str(num))\n",
    "push(stack, str(num1))\n",
    "push(stack, str(num2))\n",
    "push(stack, str(num3))\n",
    "print(\"before stack: \" + str(stack))\n",
    "print(\"popped: \" + pop(stack))\n",
    "print(\"after stack: \" + str(stack))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "03bcedaf",
   "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>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Fare</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>156.000000</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>126.000000</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>156.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>78.500000</td>\n",
       "      <td>0.346154</td>\n",
       "      <td>2.423077</td>\n",
       "      <td>28.141508</td>\n",
       "      <td>0.615385</td>\n",
       "      <td>0.397436</td>\n",
       "      <td>28.109587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>45.177428</td>\n",
       "      <td>0.477275</td>\n",
       "      <td>0.795459</td>\n",
       "      <td>14.613880</td>\n",
       "      <td>1.056235</td>\n",
       "      <td>0.870146</td>\n",
       "      <td>39.401047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.830000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>39.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>19.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.003150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>78.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>14.454200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>117.250000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>35.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>30.371850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>156.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>71.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>263.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       PassengerId    Survived      Pclass         Age       SibSp  \\\n",
       "count   156.000000  156.000000  156.000000  126.000000  156.000000   \n",
       "mean     78.500000    0.346154    2.423077   28.141508    0.615385   \n",
       "std      45.177428    0.477275    0.795459   14.613880    1.056235   \n",
       "min       1.000000    0.000000    1.000000    0.830000    0.000000   \n",
       "25%      39.750000    0.000000    2.000000   19.000000    0.000000   \n",
       "50%      78.500000    0.000000    3.000000   26.000000    0.000000   \n",
       "75%     117.250000    1.000000    3.000000   35.000000    1.000000   \n",
       "max     156.000000    1.000000    3.000000   71.000000    5.000000   \n",
       "\n",
       "            Parch        Fare  \n",
       "count  156.000000  156.000000  \n",
       "mean     0.397436   28.109587  \n",
       "std      0.870146   39.401047  \n",
       "min      0.000000    6.750000  \n",
       "25%      0.000000    8.003150  \n",
       "50%      0.000000   14.454200  \n",
       "75%      0.000000   30.371850  \n",
       "max      5.000000  263.000000  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#2 Download the Titanic Dataset and perform classification using Logistic regression and decision tree.\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "from sklearn import tree\n",
    "from sklearn import metrics\n",
    "import matplotlib.pyplot as plt \n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.metrics import classification_report, confusion_matrix\n",
    "\n",
    "plt.rcParams['figure.figsize'] = (12.0, 9.0)\n",
    "df1 = pd.read_csv('C:\\\\Users\\\\KIIT\\\\Downloads\\\\titanic.csv', sep='\\t')\n",
    "df1.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "41e43d39",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE : 0.5904437765029023 R2_SCORE:  -0.4594785059901336\n"
     ]
    },
    {
     "data": {
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x+Tk1LBsctHhf+dxmU5wZsEnDOtMZYvT8EG2tVLb1MMUO4xSaLh5Tvhezh3js4eXr+jRF/L1X0/Kg2CnfWL7Xd5c/F+sMsd4Xy/dqPsXOcovRtkURjU+juHjQAuDesva1mtpam+GPjq49mroafp4vKOt6qNzmyg3L/6V8/+9teL9Oa3y/RvEcPzBC7Sc1rPd64BqKi4w9Wm7/tcP8DPy/8v0fcofc7vvYZluz23ntnapPdeoQRPlDI3VFRFwN3JaZB/a6Fkl6se59dEHHd6IvXWGpUV0MrCrvdqiuKI+V70y1wXiSpA6zQ6BuuYYi2vx8FmcqSNLir0Yhux0CdUVmdiXykiRVY4dAkqSKskYRQT93COrzKkuSesFkchT6uUPAky0vaistmZYpf3NX3P8XvS1E6lOPTO3OiUx1OlHPKxVKkqT+TggkSepnNQoITAgkSZIJgSRJlTmGQJIk1YoJgSRJldUnIjAhkCRJJgSSJFXlGAJJklQrJgSSJFVUo4DADoEkSVV5yECSJNWKCYEkSRXV6fbHJgSSJMmEQJKkyuoTEJgQSJIkEwJJkiqrUUBgQiBJkkwIJEmqzOsQSJKkWjEhkCSpIq9DIEmSasWEQJKkquoTEJgQSJIkEwJJkiqrUUBgQiBJkuwQSJJUWWbnp5FExCsi4rKIuCUiZkbEp8r5X4mIuyPihnLardVz8ZCBJEmLr2eAIzLz+oh4CXBdRFxSLvtuZh7bbkN2CCRJqqjX1yHIzDnAnPLrxyLiFuBlVdrykIEkSTUQEWsDWwBXlbMOiYgbI+LEiFi51ePtEEiSVFV2foqISRFxbcM0qbmMiJgAnAkclpmPAj8G1gU2p0gQvt3qqXjIQJKkPpaZk4HJwy2PiKUoOgMnZ+ZZ5WPua1h+PHBeq+2YEEiSVFEXAoIRRUQAU4BbMvM7DfMnNqy2J3Bzq+diQiBJUkV9cPvj7YADgZsi4oZy3heA/SNic4o+xWzgo60askMgSdJiKjOvAGKIRReMti07BJIkVdTr0w4XJccQSJIkEwJJkiqrT0BgQiBJkkwIJEmqrEYBgQmBJEkyIZAkqbI+uA7BImNCIEmSTAgkSarK6xBIkqRaMSGQJKmq+gQEJgSSJMmEQJKkymoUEJgQSJIkEwJJkirzOgSSJKlWTAgkSarI6xBIkqRaMSGQJKmq+gQEdggkSaqqRv0BDxlIkiQTAkmSKvO0Q0mSVCsmBJIkVeRph5IkqVZMCCRJqqo+AYEJgSRJMiGQJKmyGgUEJgSSJMmEQJKkyrwOgSRJqhUTAkmSKvI6BJIkqVZMCCRJqqo+AYEJgSRJMiGQJKmyGgUEJgSSJMmEQJKkyrwOgSRJqhUTAkmSKqrTdQjsEEiSVFV9+gMeMpAkSSYEkiRVVqOAwIRAkiSZEEiSVNlAjc47NCGQJEkmBJIkVVWffMCEQJIkYUIgSVJlNRpCYEIgSZJMCCRJqqxOly42IZAkSSYEkiRVNVCfgMCEQJIkmRBIklSZYwgkSVKtmBBIklSR1yGQJEm1YkIgSVJFdRpDYIdAL3DvnDl88fOfY+7cB4gYw3v22ZcDDjyI2269laO/9mWeeOIJ1lrrZXz9mGOZMGFCr8uVemq9iSvw00O3f/b7tdeYwP8948/8+De39rAqafTsEOgFxo4by2c+dxQbbbwJ8+Y9zn777M02227HV7/0RQ7/7JFs+YatOPusMzjpxBM45NDDel2u1FN/nfMo23/+fADGRHDrj/bmvGv+0eOq1C1eh0C1tvrqa7DRxpsAsPzyE1hnnXW4//77mD17Fq/f8g0AbLvtdky75OJelin1nR03fSmz7nuMfzwwr9elqEuyC/+6pWMJQUS8BtgDeBnFLaPvAc7NzFs6tU0tenfffRe33nILr93sday3/gZMv2waO+28KxdfdCH33jun1+VJfWWvN67NGX+Y3esypEo6khBExJHAqUAAVwPXlF9PjYijOrFNLXpPzJvHEYcdymeP+gITJkzgq//5X5w69RT222cvnnhiHkstNb7XJUp9Y6mxY9jt9S/nV1f9vdelqIsyOz91S6cSgoOBTTJzQePMiPgOMBP4xlAPiohJwCSA4447jvd/aFKHylMrCxYs4PDDDmW33d/Jrm9+CwCvXmddjjv+RABmz57FjN9N72GFUn958+Zr8edZD/LPR57sdSlSJZ3qEAwAawHNXeWJ5bIhZeZkYPLgt08+05niNLLM5Ctf+iLrrLMO7//AB5+dP3fuXFZddVUGBgY4/rgfs8979+thlVJ/ec8bX+3hgiVQnS5M1KkOwWHAtIi4AxgcbvtKYD3gkA5tU4vIn66/jvPOPYf1N9iAfffaA4BPHnY4d/59NqdOPQWAXXZ9M+/ec+9elin1jWXHj2Wn107ksBOu7HUpUmWRHereRMQYYCuKQYUB3AVck5kL22zChEAaxjJlV37F/X/R20KkPvXI1AOh2Pd01AUz7+94RrDbJmt0/HlAB88yyMwBwO6yJEmLAS9MJElSRXUaQ+CFiSRJkgmBJElV1enmRiYEkiTJhECSpKocQyBJkmrFhECSpIoGHEMgSZLqxIRAkqSKHEMgSZJqxYRAkqSKahQQmBBIkiQTAkmSKuvUHYN7wYRAkiSZEEiSVNVArwtYhOwQSJJUkYcMJElSrdghkCSpouzCNJKIeEVEXBYRt0TEzIj4VDl/lYi4JCLuKP9fudVzsUMgSdLi6xngiMzcCNgG+EREbAwcBUzLzPWBaeX3I3IMgSRJFfV6DEFmzgHmlF8/FhG3AC8D9gB2LFf7GTAdOHKktkwIJEnqYxExKSKubZgmDbPe2sAWwFXAmmVnYbDTsEar7ZgQSJJUUTdOO8zMycDkkdaJiAnAmcBhmfloRIx6OyYEkiQtxiJiKYrOwMmZeVY5+76ImFgunwjc36odOwSSJFWUmR2fRhJFFDAFuCUzv9Ow6FzgoPLrg4BzWj0XDxlIkrT42g44ELgpIm4o530B+AZwekQcDNwJ7NOqITsEkiRV1OsLFWbmFcBwAwZ2GU1bHjKQJEkmBJIkVVWfOxmYEEiSJEwIJEmqbKDXgwgWIRMCSZJkQiBJUlX1yQdMCCRJEiYEkiRV1uu7HS5KJgSSJMmEQJKkqrpxt8NusUMgSVJFNTpi4CEDSZJkQiBJUmVemEiSJNWKCYEkSRXVKCAwIZAkSSYEkiRV5hgCSZJUKyYEkiRVNFCfgMCEQJIkmRBIklRZjYYQmBBIkiQTAkmSKhugPhGBCYEkSTIhkCSpKscQSJKkWjEhkCSpIq9DIEmSasWEQJKkiryXgSRJqhUTAkmSKqpRQGCHQJKkqhxUKEmSasWEQJKkirJGxwxMCCRJkgmBJElVOYZAkiTVigmBJEkVmRBIkqRaMSGQJKmipD4RgQmBJEkyIZAkqao6jSEYtkMQEY/Bs1lIlP9n+XVm5godrk2SJHXJsB2CzHxJNwuRJGlxU6MLFbY3hiAi/jUiPlh+vVpEvLqzZUmSpG5qOYYgIr4MbAlsCPwUGA/8N7BdZ0uTJKm/DdQoImgnIdgTeBcwDyAz7wE8nCBJUo20c5bB05mZEZEAEbF8h2uSJGmxUKezDNpJCE6PiOOAlSLiI8ClwPGdLUuSJHVTy4QgM4+NiDcDjwIbAF/KzEs6XpkkSX2uRkMI2r4w0U3AshTXIbipc+VIkqReaHnIICI+DFwN7AW8B7gyIj7U6cIkSep3A5kdn7qlnYTgs8AWmTkXICJWBf4AnNjJwiRJ6nd1OmTQzqDCu4DHGr5/DPhHZ8qRJEm9MNK9DA4vv7wbuCoizqEYQ7AHxSEESZKWaAO9LmARGumQweDFh/6nnAad07lyJElSL4x0c6OvdrMQSZIWN3W6dHE79zJYHfgcsAmwzOD8zNy5g3VJkqQuamdQ4cnArcCrga8Cs4FrOliTJEmLhczOT93STodg1cycAizIzN9l5oeAbTpclyRJ6qJ2rkOwoPx/TkTsDtwDvLxzJUmStHio082N2ukQHB0RKwJHAN8HVgA+3dGqJElSV7Vzc6Pzyi8fAXbqbDmSJC0+ckk4yyAivk9xIaIhZeahHalIkiR13UgJwbVdq0KSpMXQEjGGIDN/1s1CJElS77QzqFCSJA2hTglBO9chkCRJNdfXCcEyfV2d1HuPTD2w1yVISzTPMsCzDCRJqpO+PstgjYNP73UJUl+6f8q+ACy7xSE9rkTqT/P/9IOubGegK1vpDs8ykCRJbd/++EhgY7z9sSRJz6rTGIJ2b398C97+WJKk2vL2x5IkVZTZ+albvP2xJEkVDdTokIG3P5YkSd7+WJKkqmoUELR1lsFPGeICReVYAkmSVAPtHDI4r+HrZYA9KcYRSJK0RKvTaYftHDI4s/H7iJgKXNqxiiRJUtdVuX3Q+sArF3UhkiQtbmoUELQ1huAxnj+G4F6KKxdKkqSaaOeQwUu6UYgkSYubOl2HoOWVCiNiWjvzJEnS4mvYDkFELBMRqwCrRcTKEbFKOa0NrNW1CiVJ6lPZhamViDgxIu6PiJsb5n0lIu6OiBvKabdW7Yx0yOCjwGEUO//rgCjnPwr8sI0aJUlS550E/AD4edP872bmse02MmyHIDO/B3wvIj6Zmd+vVKIkSTXWD9chyMwZZXr/orRzt8OBiFhp8Jvy8MHHX+yGJUlSaxExKSKubZgmtfnQQyLixvKQwsqtVm6nQ/CRzHx48JvMfAj4SJvFSJJUWwPZ+SkzJ2fmlg3T5DZK+zGwLrA5MAf4dqsHtNMhGBMRg+MHiIixwPg2HidJknogM+/LzIWZOQAcD2zV6jHtXKnwIuD0iPgJxYDHjwEXvqhKJUmqgX4YQzCUiJiYmXPKb/cEbh5pfWivQ3AkMAn4N4ozDS6m6G1IkqQeK+8xtCPFZQLuAr4M7BgRm1N8kJ9NcebgiNq5UuEA8JNyIiL+Ffg+8IlqpUuSVA/9EBBk5v5DzJ4y2nbaurlR2cvYH3gvMAs4a7QbkiRJ/WvYDkFEbADsR9ERmAucBkRm7tSl2iRJ6mv9OoagipESgluBy4F3ZuZfASLi012pSpKkxcBAffoDI552uDfFrY4vi4jjI2IXnrt8sSRJqpGRLl18NnB2RCwPvBv4NLBmRPwYODszL+5OiZIk9ac6HTJoeWGizJyXmSdn5juAlwM3AEd1ujBJktQ97Vyp8FmZ+WBmHpeZO3eqIEmSFhf9cPvjRWVUHQJJklRPbV2HQJIkvdDAkjSGQJIk1Z8JgSRJFdUoIDAhkCRJJgSSJFW2RF2HQJIk1Z8JgSRJFdUoIDAhkCRJJgSSJFXmdQgkSVKtmBBIklRRjQICEwJJkmRCIElSZV6HQJIk1YoJgSRJFQ3UJyCwQyBJUlVJfXoEHjKQJEkmBJIkVVWjMYUmBJIkyYRAkqTKPO1QkiTVigmBJEkV1em0QxMCSZJkQiBJUlWOIZAkSbViQiBJUkU1CghMCCRJkgmBJEmVDdQoIjAhkCRJJgSSJFVVo4DAhECSJJkQSJJUmdchkCRJtWJCIElSRTUKCEwIJEmSCYEkSZXVaQyBHQJJkiqqUX/AQwaSJMmEQJKkyup0yMCEQJIkmRBIklSVCYEkSaoVEwJJkiqqUUBgQiBJkkwIJEmqzDEEkiSpVkwIJEmqqEYBgQmBJEkyIZAkqTLHEEiSpFoxIZAkqaIaBQQmBJIkyYRAkqTKHEMgSZJqxYRAkqSKahQQmBBIkiQTAkmSKqvTGAI7BJIkVVSj/oCHDCRJkgmBJEmV1emQgQmBJEkyIZAkqaoaBQQmBJIkyYRAbfjomzfggO1fTQK33PUInzrxap56ZqDXZUl9Yenx47h0ymGMHz+OcWPHcvalf+Lon1zQ67LUJXUaQ2CHQCN66UrL8uFd1mP7/7iIJxcs5PiPbcu7t34lp/1+dq9Lk/rCU08/w9sm/X/mzX+acePG8NsTD+fi3/+Fq2+a3evSpFGxQ6CWxo0dwzLjx7Jg4QDLjh/LfQ/P73VJUl+ZN/9pAJYaN5Zx48bW6lOjRlant9oOgUZ078Pz+dFFt/GnY3Zn/oKF/G7mfUyfeV+vy5L6ypgxwR9OOZJ1X7E6x502g2tu/nuvS5JGreuDCiPig93epqpbcbmleNvma7HlkRew2RG/Zrmlx/GebV7Z67KkvjIwkGyz3zdY763/zpabvoqN153Y65LUJZnZ8albenGWwVeHWxARkyLi2oi4dvLkyd2sScPYYeM1ufOBecx9/CmeWZicf91dvGG91XpdltSXHnl8PjOuvYO3vHHjXpcijVpHDhlExI3DLQLWHO5xmTkZGOwJ5L9fdfqiLk2jdPfcJ3j9Oquy7PixzH96IdtvtCY3zH6w12VJfWO1lSewYMFCHnl8PsssvRQ7b70h3z7p0l6XpS6p03iRTo0hWBN4K/BQ0/wA/tChbaoDrp/1IOdddxeXfunNPDOQ3HznQ/xixt96XZbUN1662goc/7UDGTtmDGPGBGdecj2/ufzmXpcljVqnOgTnARMy84bmBRExvUPbVIccc85MjjlnZq/LkPrSzXfcw7b7f7PXZahHahQQdKZDkJkHj7DsfZ3YpiRJqs7TDiVJqqhOYwi8l4EkSTIhkCSpqhoFBCYEkiTJDoEkSZUNDGTHp1Yi4sSIuD8ibm6Yt0pEXBIRd5T/r9yqHTsEkiQt3k4C3tY07yhgWmauD0wrvx+RHQJJkirK7PzUuoacATRfQnYP4Gfl1z8D3t2qHQcVSpJUUTdOO4yIScCkhlmTy0v9j2TNzJwDkJlzImKNVtuxQyBJUh9rus9Px9ghkCSpoj4+7fC+iJhYpgMTgftbPcAxBJIk1c+5wEHl1wcB57R6gAmBJEkV9cOliyNiKrAjsFpE3AV8GfgGcHpEHAzcCezTqh07BJIkLcYyc/9hFu0ymnbsEEiSVFEfBASLjGMIJEmSCYEkSVX1wxiCRcWEQJIkmRBIklSVCYEkSaoVEwJJkqqqT0BgQiBJkkwIJEmqzDEEkiSpVkwIJEmqyIRAkiTVigmBJEkVmRBIkqRaMSGQJKmiOiUEdggkSaqqPv0BDxlIkiQTAkmSKqvTIQMTAkmSZEIgSVJVJgSSJKlWTAgkSarIhECSJNWKCYEkSVXVJyAwIZAkSSYEkiRV5hgCSZJUKyYEkiRVZEIgSZJqxYRAkqSKTAgkSVKtmBBIklSRCYEkSaoVEwJJkqqqT0BgQiBJkkwIJEmqrE5jCOwQSJJUUZ06BB4ykCRJJgSSJFVlQiBJkmrFhECSpKrqExCYEEiSJBMCSZIqcwyBJEmqFRMCSZIqMiGQJEm1YkIgSVJFJgSSJKlWTAgkSarIhECSJNWKCYEkSVXVJyAwIZAkSSYEkiRV5hgCSZJUKyYEkiRVZEIgSZJqxYRAkqSK6pQQ2CGQJKmiOnUIPGQgSZJMCCRJqqw+AYEJgSRJMiGQJKkyxxBIkqRaMSGQJKkiEwJJklQrJgSSJFVlQiBJkurEhECSpKpyoNcVLDImBJIkyYRAkqTKHEMgSZLqxIRAkqSqHEMgSZLqxIRAkqSqHEMgSZLqxIRAkqSqHEMgSZLqxIRAkqSqTAgkSVKdmBBIklRVjc4ysEMgSVJVNTpk0Ncdgvun7NvrEqS+Nv9PP+h1CZJqop87BNHrAvR8ETEpMyf3ug6pX/k7sgSq0SEDBxVqNCb1ugCpz/k7osVWPycEkiT1N8cQSJKkfhARs4HHgIXAM5m5ZZV27BBoNDw2Ko3M35ElTf+MIdgpMx94MQ04hkBtc7CUNDJ/R7Q4s0MgSVJVOdDxKSImRcS1DVPz4NUELo6I64ZY1jYPGUiS1MfK5Gmk9Gm7zLwnItYALomIWzNzxmi3Y0KgliLibRFxW0T8NSKO6nU9Uj+JiBMj4v6IuLnXtagHMjs/tSwh7yn/vx84G9iqylOxQ6ARRcRY4IfA24GNgf0jYuPeViX1lZOAt/W6CC2ZImL5iHjJ4NfAW4BKnVMPGaiVrYC/ZubfACLiVGAP4C89rUrqE5k5IyLW7nUd6pHeX4dgTeDsiIBin35KZl5YpSE7BGrlZcA/Gr6/C9i6R7VIkhqUH9ZetyjaskOgVoa6p0TfnHgrST3VP9cheNEcQ6BW7gJe0fD9y4F7elSLJKlDTAjUyjXA+hHxauBuYD/gfb0tSZL6RO/HECwyJgQaUWY+AxwCXATcApyemTN7W5XUPyJiKvBHYMOIuCsiDu51TVIVJgRqKTMvAC7odR1SP8rM/Xtdg3powDEEkiSpRkwIJEmqqkZjCOwQSJJUVY06BB4ykCRJJgSSJFXmhYmkJU9ELIyIGyLi5oj4ZUQs9yLaOiki3lN+fcJIN4yKiB0j4o0VtjE7IlZrd37TOo+PcltfiYjPjLZGSf3DDoHUvvmZuXlmbgo8DXyscWF5Z8hRy8wPZ+ZIN4vaERh1h0BSF+RA56cusUMgVXM5sF756f2yiDgFuCkixkbEtyLimoi4MSI+ChCFH0TEXyLifGCNwYYiYnpEbFl+/baIuD4i/hwR08q76H0M+HSZTmwfEatHxJnlNq6JiO3Kx64aERdHxJ8i4jiGvg/F80TEryLiuoiYGRGTmpZ9u6xlWkSsXs5bNyIuLB9zeUS8ZpG8mpJ6zjEE0ihFxDjg7cDgLUa3AjbNzFnlTvWRzHxDRCwN/D4iLga2ADYEXktxu9K/ACc2tbs6cDywQ9nWKpn5YET8BHg8M48t1zsF+G5mXhERr6S4iuRGwJeBKzLzaxGxO/C8HfwwPlRuY1ngmog4MzPnAssD12fmERHxpbLtQ4DJwMcy846I2Br4EbBzhZdRqocajSGwQyC1b9mIuKH8+nJgCkWUf3VmzirnvwXYbHB8ALAisD6wAzA1MxcC90TEb4dofxtgxmBbmfngMHXsCmxc3v8cYIWIeEm5jb3Kx54fEQ+18ZwOjYg9y69fUdY6FxgATivn/zdwVkRMKJ/vLxu2vXQb25C0GLBDILVvfmZu3jij3DHOa5wFfDIzL2pabzda3zY62lgHikN922bm/CFqafvjSkTsSNG52DYzn4iI6cAyw6ye5XYfbn4NpCWa1yGQNIyLgH+LiKUAImKDiFgemAHsV44xmAjsNMRj/wi8qbyzJBGxSjn/MeAlDetdTBHfU663efnlDOCAct7bgZVb1Loi8FDZGXgNRUIxaAwwmHK8j+JQxKPArIjYp9xGRMTrWmxD0mLCDoG0aJ1AMT7g+oi4GTiOIok7G7gDuAn4MfC75gdm5j8pjvufFRF/5rnI/tfAnoODCoFDgS3LQYt/4bmzHb4K7BAR11McurizRa0XAuMi4kbgP4ErG5bNAzaJiOsoxgh8rZx/AHBwWd9MYI82XhOpvjI7P3VJZI0GREiS1E3LbnNkx3ei86/8ZsszhhYFxxBIklSVYwgkSVKdmBBIklRVjQ67mxBIkiQTAkmSKnMMgSRJqhMTAkmSqnIMgSRJqhMTAkmSqqrRGAI7BJIkVeUhA0mSVCcmBJIkVVWjQwYmBJIkybsdSpIkEwJJkoQdAkmShB0CSZKEHQJJkoQdAkmShB0CSZIE/C/wWV2rC2x8TgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 648x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "X = df1.iloc[:, 0:1].values\n",
    "Y = df1.iloc[:, 1].values \n",
    "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.3, random_state=0)\n",
    "\n",
    "\n",
    "# Logistic Regression\n",
    "classifier3 = LogisticRegression(solver='lbfgs', max_iter=1000)\n",
    "classifier3.fit(X_train,Y_train)\n",
    "\n",
    "p_model = classifier3.predict(X_test)\n",
    "score = classifier3.score(X_test, Y_test.astype(int))\n",
    "cm = metrics.confusion_matrix(Y_test.astype(int), p_model)\n",
    "\n",
    "plt.figure(figsize=(9,9))\n",
    "sns.heatmap(cm, annot=True, linewidths=.5, square = True, cmap = 'Blues_r');\n",
    "plt.ylabel('Actual label');\n",
    "plt.xlabel('Predicted label');\n",
    "all_sample_title = 'Accuracy Score: {0}'.format(score)\n",
    "plt.title(all_sample_title, size = 15);\n",
    "\n",
    "y_train_predict2 = classifier3.predict(X_train)\n",
    "rmse2=(np.sqrt(mean_squared_error(Y_train.astype(int),y_train_predict2)))\n",
    "r2_2=r2_score(Y_train.astype(int),y_train_predict2)\n",
    "print('RMSE :',rmse2,'R2_SCORE: ',r2_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6f42d7a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.574468085106383\n",
      "[[19 17]\n",
      " [ 3  8]]\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.86      0.53      0.66        36\n",
      "           1       0.32      0.73      0.44        11\n",
      "\n",
      "    accuracy                           0.57        47\n",
      "   macro avg       0.59      0.63      0.55        47\n",
      "weighted avg       0.74      0.57      0.61        47\n",
      "\n",
      "Mean Absolute Error: 0.425531914893617\n",
      "Mean Squared Error: 0.425531914893617\n",
      "Root Mean Squared Error: 0.6523280730534422\n"
     ]
    }
   ],
   "source": [
    "#Decision Tree\n",
    "\n",
    "model = DecisionTreeClassifier()\n",
    "model.fit(X_train,Y_train)\n",
    "Y_pred=model.predict(X_test)\n",
    "accuracy=metrics.accuracy_score(Y_test,Y_pred)\n",
    "print(accuracy)\n",
    "print(confusion_matrix(Y_test, Y_pred))\n",
    "print(classification_report(Y_test, Y_pred))\n",
    "print('Mean Absolute Error:', metrics.mean_absolute_error(Y_test, Y_pred))\n",
    "print('Mean Squared Error:', metrics.mean_squared_error(Y_test, Y_pred))\n",
    "print('Root Mean Squared Error:', np.sqrt(metrics.mean_squared_error(Y_test, Y_pred)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9e625dde",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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\n",
      "text/plain": [
       "<Figure size 864x648 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tree.plot_tree(model,filled = True)"
   ]
  }
 ],
 "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}