21 Decision_tree_clf_jun26.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "689c0c4d-9330-427e-8081-5bbb87172bb7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# dataset: banknotes.csv\n",
    "# location: https://mitu.co.in/dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "eb7c8c0f-d727-4dee-8d2f-2d90ca9f911e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d9059c33-c800-49e9-b944-f8996dd654d9",
   "metadata": {},
   "outputs": [
    {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Variance</th>\n",
       "      <th>Skewness</th>\n",
       "      <th>Curtosis</th>\n",
       "      <th>Entropy</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.62160</td>\n",
       "      <td>8.66610</td>\n",
       "      <td>-2.8073</td>\n",
       "      <td>-0.44699</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.54590</td>\n",
       "      <td>8.16740</td>\n",
       "      <td>-2.4586</td>\n",
       "      <td>-1.46210</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.86600</td>\n",
       "      <td>-2.63830</td>\n",
       "      <td>1.9242</td>\n",
       "      <td>0.10645</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.45660</td>\n",
       "      <td>9.52280</td>\n",
       "      <td>-4.0112</td>\n",
       "      <td>-3.59440</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.32924</td>\n",
       "      <td>-4.45520</td>\n",
       "      <td>4.5718</td>\n",
       "      <td>-0.98880</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367</th>\n",
       "      <td>0.40614</td>\n",
       "      <td>1.34920</td>\n",
       "      <td>-1.4501</td>\n",
       "      <td>-0.55949</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1368</th>\n",
       "      <td>-1.38870</td>\n",
       "      <td>-4.87730</td>\n",
       "      <td>6.4774</td>\n",
       "      <td>0.34179</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1369</th>\n",
       "      <td>-3.75030</td>\n",
       "      <td>-13.45860</td>\n",
       "      <td>17.5932</td>\n",
       "      <td>-2.77710</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1370</th>\n",
       "      <td>-3.56370</td>\n",
       "      <td>-8.38270</td>\n",
       "      <td>12.3930</td>\n",
       "      <td>-1.28230</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1371</th>\n",
       "      <td>-2.54190</td>\n",
       "      <td>-0.65804</td>\n",
       "      <td>2.6842</td>\n",
       "      <td>1.19520</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1372 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Variance  Skewness  Curtosis  Entropy  Class\n",
       "0      3.62160   8.66610   -2.8073 -0.44699      0\n",
       "1      4.54590   8.16740   -2.4586 -1.46210      0\n",
       "2      3.86600  -2.63830    1.9242  0.10645      0\n",
       "3      3.45660   9.52280   -4.0112 -3.59440      0\n",
       "4      0.32924  -4.45520    4.5718 -0.98880      0\n",
       "...        ...       ...       ...      ...    ...\n",
       "1367   0.40614   1.34920   -1.4501 -0.55949      1\n",
       "1368  -1.38870  -4.87730    6.4774  0.34179      1\n",
       "1369  -3.75030 -13.45860   17.5932 -2.77710      1\n",
       "1370  -3.56370  -8.38270   12.3930 -1.28230      1\n",
       "1371  -2.54190  -0.65804    2.6842  1.19520      1\n",
       "\n",
       "[1372 rows x 5 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('banknotes.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e2f58d2d-5b48-44c9-a775-e68aabce3b54",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1372, 5)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8ac11d18-fa6d-489f-957e-e5548a5bb6fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Variance    0\n",
       "Skewness    0\n",
       "Curtosis    0\n",
       "Entropy     0\n",
       "Class       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "badf059b-5b16-48e6-929d-4f230f92c3c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# separate input and output\n",
    "\n",
    "x = df.drop('Class', axis = 1)\n",
    "\n",
    "y = df['Class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "59504a02-fab5-4f43-be86-66e2a640ab1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Variance</th>\n",
       "      <th>Skewness</th>\n",
       "      <th>Curtosis</th>\n",
       "      <th>Entropy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.62160</td>\n",
       "      <td>8.66610</td>\n",
       "      <td>-2.8073</td>\n",
       "      <td>-0.44699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.54590</td>\n",
       "      <td>8.16740</td>\n",
       "      <td>-2.4586</td>\n",
       "      <td>-1.46210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.86600</td>\n",
       "      <td>-2.63830</td>\n",
       "      <td>1.9242</td>\n",
       "      <td>0.10645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.45660</td>\n",
       "      <td>9.52280</td>\n",
       "      <td>-4.0112</td>\n",
       "      <td>-3.59440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.32924</td>\n",
       "      <td>-4.45520</td>\n",
       "      <td>4.5718</td>\n",
       "      <td>-0.98880</td>\n",
       "    </tr>\n",
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       "    <tr>\n",
       "      <th>1367</th>\n",
       "      <td>0.40614</td>\n",
       "      <td>1.34920</td>\n",
       "      <td>-1.4501</td>\n",
       "      <td>-0.55949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1368</th>\n",
       "      <td>-1.38870</td>\n",
       "      <td>-4.87730</td>\n",
       "      <td>6.4774</td>\n",
       "      <td>0.34179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1369</th>\n",
       "      <td>-3.75030</td>\n",
       "      <td>-13.45860</td>\n",
       "      <td>17.5932</td>\n",
       "      <td>-2.77710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1370</th>\n",
       "      <td>-3.56370</td>\n",
       "      <td>-8.38270</td>\n",
       "      <td>12.3930</td>\n",
       "      <td>-1.28230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1371</th>\n",
       "      <td>-2.54190</td>\n",
       "      <td>-0.65804</td>\n",
       "      <td>2.6842</td>\n",
       "      <td>1.19520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1372 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Variance  Skewness  Curtosis  Entropy\n",
       "0      3.62160   8.66610   -2.8073 -0.44699\n",
       "1      4.54590   8.16740   -2.4586 -1.46210\n",
       "2      3.86600  -2.63830    1.9242  0.10645\n",
       "3      3.45660   9.52280   -4.0112 -3.59440\n",
       "4      0.32924  -4.45520    4.5718 -0.98880\n",
       "...        ...       ...       ...      ...\n",
       "1367   0.40614   1.34920   -1.4501 -0.55949\n",
       "1368  -1.38870  -4.87730    6.4774  0.34179\n",
       "1369  -3.75030 -13.45860   17.5932 -2.77710\n",
       "1370  -3.56370  -8.38270   12.3930 -1.28230\n",
       "1371  -2.54190  -0.65804    2.6842  1.19520\n",
       "\n",
       "[1372 rows x 4 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "86b83b0e-6e63-4c0c-a062-8ccc3dc883ce",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "058c6cfc-c62d-4849-b134-0db97165d866",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Class\n",
       "0    762\n",
       "1    610\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Class'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "2d7b7141-a9e6-404d-995d-39a0fe0bad58",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DQeXm5uqLL75QMBiUJHm93oj3eL1e+1wwGFR8fLzGjBlzwjnHU1ZWJo/HYx/p6enDvDMAABAtHI2dOXPm6KabblJ2drby8vL0wgsvSPrLx1VHuVyuiPdYljVo7FjfNqekpEShUMg+2traTmEXAAAgmjn+MdZfS0xMVHZ2tj7++GP7OZ5j79B0dHTYd3t8Pp/6+vrU2dl5wjnH43a7lZycHHEAAAAzRVXshMNhffDBBzr//POVkZEhn8+n+vp6+3xfX58aGhqUm5srScrJyVFcXFzEnPb2du3bt8+eAwAAzm6O/jTWypUrNW/ePI0fP14dHR166KGH1NXVpUWLFsnlcikQCKi0tFSZmZnKzMxUaWmpRo0apYULF0qSPB6PFi9erKKiIqWmpiolJUUrV660PxYDAABwNHYOHjyoW2+9VZ9//rnGjh2rf/qnf9Lu3bt14YUXSpKKi4vV29urwsJCdXZ2aurUqdqxY4eSkpLsa1RUVCg2NlYFBQXq7e3VzJkzVV1drZiYGKe2BQAAoojLsizL6UU4raurSx6PR6FQaESf38m57+kRuzZwpmp+5A6nlzAsWh/MdnoJQNQZf//eb590Ck72+3dUPbMDAAAw3IgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYLQhxc7111+vQ4cODRrv6urS9ddff6prAgAAGDZDip3XXntNfX19g8b//Oc/64033jjlRQEAAAyX2O8y+b333rP/+/3331cwGLRfDwwM6OWXX9bf/M3fDN/qAAAATtF3ip2///u/l8vlksvlOu7HVQkJCXr88ceHbXEAAACn6jvFTktLiyzL0oQJE/TWW29p7Nix9rn4+HiNGzdOMTExw75IAACAofpOsXPhhRdKko4cOTIiiwEAABhu3yl2/tpHH32k1157TR0dHYPi5/777z/lhQEAAAyHIcXOk08+qR//+MdKS0uTz+eTy+Wyz7lcLmIHAABEjSHFzkMPPaT169dr1apVw70eAACAYTWk37PT2dmpm2++ebjXAgAAMOyGFDs333yzduzYMdxrAQAAGHZD+hjr4osv1po1a7R7925lZ2crLi4u4vw999wzLIsDAAA4VUOKnc2bN2v06NFqaGhQQ0NDxDmXy0XsAACAqDGkj7FaWlpOeHz22WdDWkhZWZlcLpcCgYA9ZlmW1q5dK7/fr4SEBM2YMUP79++PeF84HNby5cuVlpamxMREzZ8/XwcPHhzSGgAAgHmGFDvDrampSZs3b9bll18eMV5eXq4NGzaoqqpKTU1N8vl8mjVrlrq7u+05gUBAdXV1qq2t1a5du9TT06O5c+dqYGDgdG8DAABEoSF9jHXnnXd+4/mf//znJ32tnp4e3XbbbXryySf10EMP2eOWZamyslKrV6/WggULJElbt26V1+vV9u3btXTpUoVCIW3ZskXbtm1TXl6eJKmmpkbp6enauXOnZs+ePYTdAQAAkwz5R8//+ujo6NCrr76qX/3qVzp06NB3utayZct0ww032LFyVEtLi4LBoPLz8+0xt9ut6dOnq7GxUZLU3Nys/v7+iDl+v19ZWVn2nOMJh8Pq6uqKOAAAgJmGdGenrq5u0NiRI0dUWFioCRMmnPR1amtr9c4776ipqWnQuWAwKEnyer0R416vVwcOHLDnxMfHa8yYMYPmHH3/8ZSVlWndunUnvU4AAHDmGrZnds455xzde++9qqioOKn5bW1t+rd/+zfV1NTo3HPPPeG8v/5TFNJfPt46duxY3zanpKREoVDIPtra2k5qzQAA4MwzrA8of/rpp/r6669Pam5zc7M6OjqUk5Oj2NhYxcbGqqGhQY899phiY2PtOzrH3qHp6Oiwz/l8PvX19amzs/OEc47H7XYrOTk54gAAAGYa0sdYK1asiHhtWZba29v1wgsvaNGiRSd1jZkzZ2rv3r0RY//6r/+qSy65RKtWrdKECRPk8/lUX1+vyZMnS5L6+vrU0NCghx9+WJKUk5OjuLg41dfXq6CgQJLU3t6uffv2qby8fChbAwAAhhlS7Lz77rsRr8855xyNHTtWjz766Lf+pNZRSUlJysrKihhLTExUamqqPR4IBFRaWqrMzExlZmaqtLRUo0aN0sKFCyVJHo9HixcvVlFRkVJTU5WSkqKVK1cqOzt70APPAADg7DSk2Pnd73433Os4ruLiYvX29qqwsFCdnZ2aOnWqduzYoaSkJHtORUWFYmNjVVBQoN7eXs2cOVPV1dWKiYk5LWsEAADRzWVZljXUN//pT3/Shx9+KJfLpYkTJ2rs2LHDubbTpqurSx6PR6FQaESf38m57+kRuzZwpmp+5A6nlzAsWh/MdnoJQNQZf//eb590Ck72+/eQHlA+fPiw7rzzTp1//vm69tprdc0118jv92vx4sX66quvhrxoAACA4Tak2FmxYoUaGhr03//93zp06JAOHTqkX//612poaFBRUdFwrxEAAGDIhvTMzi9/+Us9++yzmjFjhj32ve99TwkJCSooKNCmTZuGa30AAACnZEh3dr766qvj/h6bcePG8TEWAACIKkOKnWnTpumBBx7Qn//8Z3ust7dX69at07Rp04ZtcQAAAKdqSB9jVVZWas6cObrgggt0xRVXyOVyac+ePXK73dqxY8dwrxEAAGDIhhQ72dnZ+vjjj1VTU6M//OEPsixLt9xyi2677TYlJCQM9xoBAACGbEixU1ZWJq/Xqx/96EcR4z//+c/1pz/9SatWrRqWxQEAAJyqIT2z81//9V+65JJLBo1PmjRJTzzxxCkvCgAAYLgMKXaCwaDOP//8QeNjx45Ve3v7KS8KAABguAwpdtLT0/Xmm28OGn/zzTfl9/tPeVEAAADDZUjP7CxZskSBQED9/f26/vrrJUm//e1vVVxczG9QBgAAUWVIsVNcXKwvv/xShYWF6uvrkySde+65WrVqlUpKSoZ1gQAAAKdiSLHjcrn08MMPa82aNfrggw+UkJCgzMxMud3u4V4fAADAKRlS7Bw1evRoXXnllcO1FgAAgGE3pAeUAQAAzhTEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjORo7mzZt0uWXX67k5GQlJydr2rRpeumll+zzlmVp7dq18vv9SkhI0IwZM7R///6Ia4TDYS1fvlxpaWlKTEzU/PnzdfDgwdO9FQAAEKUcjZ0LLrhAP/vZz/T222/r7bff1vXXX6/vf//7dtCUl5drw4YNqqqqUlNTk3w+n2bNmqXu7m77GoFAQHV1daqtrdWuXbvU09OjuXPnamBgwKltAQCAKOJo7MybN0/f+973NHHiRE2cOFHr16/X6NGjtXv3blmWpcrKSq1evVoLFixQVlaWtm7dqq+++krbt2+XJIVCIW3ZskWPPvqo8vLyNHnyZNXU1Gjv3r3auXOnk1sDAABRImqe2RkYGFBtba0OHz6sadOmqaWlRcFgUPn5+fYct9ut6dOnq7GxUZLU3Nys/v7+iDl+v19ZWVn2nOMJh8Pq6uqKOAAAgJkcj529e/dq9OjRcrvduuuuu1RXV6fLLrtMwWBQkuT1eiPme71e+1wwGFR8fLzGjBlzwjnHU1ZWJo/HYx/p6enDvCsAABAtHI+dv/u7v9OePXu0e/du/fjHP9aiRYv0/vvv2+ddLlfEfMuyBo0d69vmlJSUKBQK2UdbW9upbQIAAEQtx2MnPj5eF198saZMmaKysjJdccUV+o//+A/5fD5JGnSHpqOjw77b4/P51NfXp87OzhPOOR63223/BNjRAwAAmMnx2DmWZVkKh8PKyMiQz+dTfX29fa6vr08NDQ3Kzc2VJOXk5CguLi5iTnt7u/bt22fPAQAAZ7dYJ7/4v//7v2vOnDlKT09Xd3e3amtr9dprr+nll1+Wy+VSIBBQaWmpMjMzlZmZqdLSUo0aNUoLFy6UJHk8Hi1evFhFRUVKTU1VSkqKVq5cqezsbOXl5Tm5NQAAECUcjZ0//vGPuv3229Xe3i6Px6PLL79cL7/8smbNmiVJKi4uVm9vrwoLC9XZ2ampU6dqx44dSkpKsq9RUVGh2NhYFRQUqLe3VzNnzlR1dbViYmKc2hYAAIgiLsuyLKcX4bSuri55PB6FQqERfX4n576nR+zawJmq+ZE7nF7CsGh9MNvpJQBRZ/z9e0f0+if7/TvqntkBAAAYTsQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjEbsAAAAoxE7AADAaMQOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwAAwGjEDgAAMBqxAwAAjOZo7JSVlenKK69UUlKSxo0bpxtvvFEffvhhxBzLsrR27Vr5/X4lJCRoxowZ2r9/f8SccDis5cuXKy0tTYmJiZo/f74OHjx4OrcCAACilKOx09DQoGXLlmn37t2qr6/X119/rfz8fB0+fNieU15erg0bNqiqqkpNTU3y+XyaNWuWuru77TmBQEB1dXWqra3Vrl271NPTo7lz52pgYMCJbQEAgCgS6+QXf/nllyNeP/XUUxo3bpyam5t17bXXyrIsVVZWavXq1VqwYIEkaevWrfJ6vdq+fbuWLl2qUCikLVu2aNu2bcrLy5Mk1dTUKD09XTt37tTs2bNP+74AAED0iKpndkKhkCQpJSVFktTS0qJgMKj8/Hx7jtvt1vTp09XY2ChJam5uVn9/f8Qcv9+vrKwse86xwuGwurq6Ig4AAGCmqIkdy7K0YsUKXX311crKypIkBYNBSZLX642Y6/V67XPBYFDx8fEaM2bMCeccq6ysTB6Pxz7S09OHezsAACBKRE3s3H333Xrvvff0i1/8YtA5l8sV8dqyrEFjx/qmOSUlJQqFQvbR1tY29IUDAICoFhWxs3z5cj3//PP63e9+pwsuuMAe9/l8kjToDk1HR4d9t8fn86mvr0+dnZ0nnHMst9ut5OTkiAMAAJjJ0dixLEt33323fvWrX+nVV19VRkZGxPmMjAz5fD7V19fbY319fWpoaFBubq4kKScnR3FxcRFz2tvbtW/fPnsOAAA4ezn601jLli3T9u3b9etf/1pJSUn2HRyPx6OEhAS5XC4FAgGVlpYqMzNTmZmZKi0t1ahRo7Rw4UJ77uLFi1VUVKTU1FSlpKRo5cqVys7Otn86CwAAnL0cjZ1NmzZJkmbMmBEx/tRTT+mHP/yhJKm4uFi9vb0qLCxUZ2enpk6dqh07digpKcmeX1FRodjYWBUUFKi3t1czZ85UdXW1YmJiTtdWAABAlHJZlmU5vQindXV1yePxKBQKjejzOzn3PT1i1wbOVM2P3OH0EoZF64PZTi8BiDrj7987otc/2e/fUfGAMgAAwEghdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0R2Pn9ddf17x58+T3++VyufTcc89FnLcsS2vXrpXf71dCQoJmzJih/fv3R8wJh8Navny50tLSlJiYqPnz5+vgwYOncRcAACCaORo7hw8f1hVXXKGqqqrjni8vL9eGDRtUVVWlpqYm+Xw+zZo1S93d3facQCCguro61dbWateuXerp6dHcuXM1MDBwurYBAACiWKyTX3zOnDmaM2fOcc9ZlqXKykqtXr1aCxYskCRt3bpVXq9X27dv19KlSxUKhbRlyxZt27ZNeXl5kqSamhqlp6dr586dmj179mnbCwAAiE5R+8xOS0uLgsGg8vPz7TG3263p06ersbFRktTc3Kz+/v6IOX6/X1lZWfYcAABwdnP0zs43CQaDkiSv1xsx7vV6deDAAXtOfHy8xowZM2jO0fcfTzgcVjgctl93dXUN17IBAECUido7O0e5XK6I15ZlDRo71rfNKSsrk8fjsY/09PRhWSsAAIg+URs7Pp9Pkgbdoeno6LDv9vh8PvX19amzs/OEc46npKREoVDIPtra2oZ59QAAIFpEbexkZGTI5/Opvr7eHuvr61NDQ4Nyc3MlSTk5OYqLi4uY097ern379tlzjsftdis5OTniAAAAZnL0mZ2enh598skn9uuWlhbt2bNHKSkpGj9+vAKBgEpLS5WZmanMzEyVlpZq1KhRWrhwoSTJ4/Fo8eLFKioqUmpqqlJSUrRy5UplZ2fbP50FAADObo7Gzttvv63rrrvOfr1ixQpJ0qJFi1RdXa3i4mL19vaqsLBQnZ2dmjp1qnbs2KGkpCT7PRUVFYqNjVVBQYF6e3s1c+ZMVVdXKyYm5rTvBwAARB+XZVmW04twWldXlzwej0Kh0Ih+pJVz39Mjdm3gTNX8yB1OL2FYtD6Y7fQSgKgz/v69I3r9k/3+HbXP7AAAAAwHYgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEYjdgAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRjImdjRs3KiMjQ+eee65ycnL0xhtvOL0kAAAQBYyInWeeeUaBQECrV6/Wu+++q2uuuUZz5sxRa2ur00sDAAAOMyJ2NmzYoMWLF2vJkiW69NJLVVlZqfT0dG3atMnppQEAAIfFOr2AU9XX16fm5mb95Cc/iRjPz89XY2Pjcd8TDocVDoft16FQSJLU1dU1cguVNBDuHdHrA2eikf53d7p0/3nA6SUAUWek/30fvb5lWd8474yPnc8//1wDAwPyer0R416vV8Fg8LjvKSsr07p16waNp6enj8gaAZyY5/G7nF4CgJFS5jktX6a7u1sez4m/1hkfO0e5XK6I15ZlDRo7qqSkRCtWrLBfHzlyRF9++aVSU1NP+B6Yo6urS+np6Wpra1NycrLTywEwjPj3fXaxLEvd3d3y+/3fOO+Mj520tDTFxMQMuovT0dEx6G7PUW63W263O2LsvPPOG6klIkolJyfzP4aAofj3ffb4pjs6R53xDyjHx8crJydH9fX1EeP19fXKzc11aFUAACBanPF3diRpxYoVuv322zVlyhRNmzZNmzdvVmtrq+66i2cBAAA42xkROz/4wQ/0xRdf6MEHH1R7e7uysrL04osv6sILL3R6aYhCbrdbDzzwwKCPMgGc+fj3jeNxWd/281oAAABnsDP+mR0AAIBvQuwAAACjETsAAMBoxA4AADAasYOzysaNG5WRkaFzzz1XOTk5euONN5xeEoBh8Prrr2vevHny+/1yuVx67rnnnF4Sogixg7PGM888o0AgoNWrV+vdd9/VNddcozlz5qi1tdXppQE4RYcPH9YVV1yhqqoqp5eCKMSPnuOsMXXqVP3DP/yDNm3aZI9deumluvHGG1VWVubgygAMJ5fLpbq6Ot14441OLwVRgjs7OCv09fWpublZ+fn5EeP5+flqbGx0aFUAgNOB2MFZ4fPPP9fAwMCgPw7r9XoH/RFZAIBZiB2cVVwuV8Rry7IGjQEAzELs4KyQlpammJiYQXdxOjo6Bt3tAQCYhdjBWSE+Pl45OTmqr6+PGK+vr1dubq5DqwIAnA5G/NVz4GSsWLFCt99+u6ZMmaJp06Zp8+bNam1t1V133eX00gCcop6eHn3yySf265aWFu3Zs0cpKSkaP368gytDNOBHz3FW2bhxo8rLy9Xe3q6srCxVVFTo2muvdXpZAE7Ra6+9puuuu27Q+KJFi1RdXX36F4SoQuwAAACj8cwOAAAwGrEDAACMRuwAAACjETsAAMBoxA4AADAasQMAAIxG7AAAAKMROwDOeC6XS88995zTywAQpYgdAFEvGAxq+fLlmjBhgtxut9LT0zVv3jz99re/dXppAM4A/G0sAFHtf/7nf3TVVVfpvPPOU3l5uS6//HL19/frlVde0bJly/SHP/zB6SUCiHLc2QEQ1QoLC+VyufTWW2/pX/7lXzRx4kRNmjRJK1as0O7du4/7nlWrVmnixIkaNWqUJkyYoDVr1qi/v98+//vf/17XXXedkpKSlJycrJycHL399tuSpAMHDmjevHkaM2aMEhMTNWnSJL344ounZa8ARgZ3dgBErS+//FIvv/yy1q9fr8TExEHnzzvvvOO+LykpSdXV1fL7/dq7d69+9KMfKSkpScXFxZKk2267TZMnT9amTZsUExOjPXv2KC4uTpK0bNky9fX16fXXX1diYqLef/99jR49esT2CGDkETsAotYnn3wiy7J0ySWXfKf3/fSnP7X/+6KLLlJRUZGeeeYZO3ZaW1t133332dfNzMy057e2tuqmm25Sdna2JGnChAmnug0ADuNjLABRy7IsSX/5aavv4tlnn9XVV18tn8+n0aNHa82aNWptbbXPr1ixQkuWLFFeXp5+9rOf6dNPP7XP3XPPPXrooYd01VVX6YEHHtB77703PJsB4BhiB0DUyszMlMvl0gcffHDS79m9e7duueUWzZkzR7/5zW/07rvvavXq1err67PnrF27Vvv379cNN9ygV199VZdddpnq6uokSUuWLNFnn32m22+/XXv37tWUKVP0+OOPD/veAJw+Luvo/3UCgCg0Z84c7d27Vx9++OGg53YOHTqk8847Ty6XS3V1dbrxxhv16KOPauPGjRF3a5YsWaJnn31Whw4dOu7XuPXWW3X48GE9//zzg86VlJTohRde4A4PcAbjzg6AqLZx40YNDAzoH//xH/XLX/5SH3/8sT744AM99thjmjZt2qD5F198sVpbW1VbW6tPP/1Ujz32mH3XRpJ6e3t1991367XXXtOBAwf05ptvqqmpSZdeeqkkKRAI6JVXXlFLS4veeecdvfrqq/Y5AGcmHlAGENUyMjL0zjvvaP369SoqKlJ7e7vGjh2rnJwcbdq0adD873//+7r33nt19913KxwO64YbbtCaNWu0du1aSVJMTIy++OIL3XHHHfrjH/+otLQ0LViwQOvWrZMkDQwMaNmyZTp48KCSk5P1z//8z6qoqDidWwYwzPgYCwAAGI2PsQAAgNGIHQAAYDRiBwAAGI3YAQAARiN2AACA0YgdAABgNGIHAAAYjdgBAABGI3YAAIDRiB0AAGA0YgcAABiN2AEAAEb7fzp8fpgG3s5zAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(x = y);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d08361e9-0d96-4246-a313-a7f18a2002f9",
   "metadata": {},
   "source": [
    "# Cross Validation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b3944be1-ab83-4798-a127-c33bb3c63460",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "625eddfb-412c-4922-a348-3a4bae656879",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(x, y,\n",
    "                                                   random_state= 0,\n",
    "                                                   test_size= 0.25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b517d023-48dd-41c1-bf29-ff04382f12ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1029, 4)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "94fead60-1eac-4d04-9b9f-f98596031dab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1029,)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8a86d9af-dfeb-47b8-93a4-f9cb7e6a6f9e",
   "metadata": {},
   "source": [
    "### build the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c3903ff9-5b04-452c-b056-59cfcc9bb896",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "28cef63a-344b-4143-b377-bdc8a0317529",
   "metadata": {},
   "outputs": [],
   "source": [
    "dt = DecisionTreeClassifier(random_state= 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "34f0493a-2e95-4d00-a0bf-cc4286473ad2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(random_state=0)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;DecisionTreeClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.tree.DecisionTreeClassifier.html\">?<span>Documentation for DecisionTreeClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>DecisionTreeClassifier(random_state=0)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "DecisionTreeClassifier(random_state=0)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "fd649d7e-c2f1-44d6-9630-a32b968b4f7b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# predict on test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "12e881dc-2be6-4874-bcaa-4d4fe8f42d81",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = dt.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "dfede053-f3b6-40e1-b943-fd31d323ffb2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 0,\n",
       "       0, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 0,\n",
       "       1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1,\n",
       "       1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0,\n",
       "       0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1,\n",
       "       0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 0, 0, 0,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0,\n",
       "       1, 0, 0, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0,\n",
       "       1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 1, 0, 1, 0, 0, 0,\n",
       "       1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0,\n",
       "       0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1,\n",
       "       1, 0, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1,\n",
       "       0, 0, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 1, 0,\n",
       "       1, 0, 0, 1, 1, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1, 1, 0, 0,\n",
       "       0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0,\n",
       "       0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_pred"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "a24c8b7f-13cf-4261-9002-5b4a50c0894b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1023    1\n",
       "642     0\n",
       "1196    1\n",
       "31      0\n",
       "253     0\n",
       "       ..\n",
       "866     1\n",
       "361     0\n",
       "703     0\n",
       "328     0\n",
       "530     0\n",
       "Name: Class, Length: 343, dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "f839b560-3756-4714-b049-bb5f7e7852de",
   "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>actual</th>\n",
       "      <th>predicted</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1023</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>642</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1196</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>866</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>361</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>703</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>328</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>343 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      actual  predicted\n",
       "1023       1          1\n",
       "642        0          0\n",
       "1196       1          1\n",
       "31         0          0\n",
       "253        0          0\n",
       "...      ...        ...\n",
       "866        1          1\n",
       "361        0          0\n",
       "703        0          0\n",
       "328        0          0\n",
       "530        0          0\n",
       "\n",
       "[343 rows x 2 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result = pd.DataFrame({\n",
    "    'actual': y_test,\n",
    "    'predicted': y_pred\n",
    "})\n",
    "\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1bc523ba-ac2f-4562-9448-d16d88c1bc2e",
   "metadata": {},
   "source": [
    "### Model Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "98801046-ff4d-4d2b-85ad-24e4f5076e15",
   "metadata": {},
   "outputs": [],
   "source": [
    "# confusion matrix\n",
    "\n",
    "from sklearn.metrics import ConfusionMatrixDisplay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "84d91efa-c61e-4dc9-a0d1-d40de7fe673e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ConfusionMatrixDisplay.from_predictions(y_test, y_pred);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "43699c07-8088-445d-87f2-492fdb1aef1e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# classification report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "b8311669-18aa-44b1-bb0d-44066a57feda",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "0897f627-c332-46e5-95f8-42059ff1c62e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      0.98      0.98       195\n",
      "           1       0.97      0.98      0.98       148\n",
      "\n",
      "    accuracy                           0.98       343\n",
      "   macro avg       0.98      0.98      0.98       343\n",
      "weighted avg       0.98      0.98      0.98       343\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test, y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "709b3c6e-a491-47e0-a0cb-418b3b628ba4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9795918367346939"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# accuracy\n",
    "\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "accuracy_score(y_test, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "347923c8-3015-41ba-89e5-9178356f999f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# visualize the tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "339e54cd-6fd1-49bd-8376-7e03109a8a57",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import plot_tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "184cf662-21d6-4ec2-9797-4889b327eb28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1300x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(13, 10))\n",
    "\n",
    "plot_tree(dt, rounded= True, class_names= ['G', 'F'], \n",
    "          feature_names= x.columns, filled= True,\n",
    "         fontsize= 7);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "15d89944-c995-408c-85dc-1b95ebb27611",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.62095248, 0.21106862, 0.14189251, 0.02608639])"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dt.feature_importances_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "8672a77b-f0b4-44a9-85c3-e7567cfc8e03",
   "metadata": {},
   "outputs": [],
   "source": [
    "# plot bar plot to visualize importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "98f68428-0cfa-4bb3-8846-5623d7b65b4c",
   "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>Variance</th>\n",
       "      <th>Skewness</th>\n",
       "      <th>Curtosis</th>\n",
       "      <th>Entropy</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.62160</td>\n",
       "      <td>8.66610</td>\n",
       "      <td>-2.8073</td>\n",
       "      <td>-0.44699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.54590</td>\n",
       "      <td>8.16740</td>\n",
       "      <td>-2.4586</td>\n",
       "      <td>-1.46210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.86600</td>\n",
       "      <td>-2.63830</td>\n",
       "      <td>1.9242</td>\n",
       "      <td>0.10645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.45660</td>\n",
       "      <td>9.52280</td>\n",
       "      <td>-4.0112</td>\n",
       "      <td>-3.59440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.32924</td>\n",
       "      <td>-4.45520</td>\n",
       "      <td>4.5718</td>\n",
       "      <td>-0.98880</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1367</th>\n",
       "      <td>0.40614</td>\n",
       "      <td>1.34920</td>\n",
       "      <td>-1.4501</td>\n",
       "      <td>-0.55949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1368</th>\n",
       "      <td>-1.38870</td>\n",
       "      <td>-4.87730</td>\n",
       "      <td>6.4774</td>\n",
       "      <td>0.34179</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1369</th>\n",
       "      <td>-3.75030</td>\n",
       "      <td>-13.45860</td>\n",
       "      <td>17.5932</td>\n",
       "      <td>-2.77710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1370</th>\n",
       "      <td>-3.56370</td>\n",
       "      <td>-8.38270</td>\n",
       "      <td>12.3930</td>\n",
       "      <td>-1.28230</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1371</th>\n",
       "      <td>-2.54190</td>\n",
       "      <td>-0.65804</td>\n",
       "      <td>2.6842</td>\n",
       "      <td>1.19520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1372 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Variance  Skewness  Curtosis  Entropy\n",
       "0      3.62160   8.66610   -2.8073 -0.44699\n",
       "1      4.54590   8.16740   -2.4586 -1.46210\n",
       "2      3.86600  -2.63830    1.9242  0.10645\n",
       "3      3.45660   9.52280   -4.0112 -3.59440\n",
       "4      0.32924  -4.45520    4.5718 -0.98880\n",
       "...        ...       ...       ...      ...\n",
       "1367   0.40614   1.34920   -1.4501 -0.55949\n",
       "1368  -1.38870  -4.87730    6.4774  0.34179\n",
       "1369  -3.75030 -13.45860   17.5932 -2.77710\n",
       "1370  -3.56370  -8.38270   12.3930 -1.28230\n",
       "1371  -2.54190  -0.65804    2.6842  1.19520\n",
       "\n",
       "[1372 rows x 4 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "71a21d95-93b7-4166-a049-37f40850f4b1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar(x.columns, dt.feature_importances_);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "id": "26fdc1da-d58f-4cf6-9e0e-2bd86fd62c11",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tkinter as tk\n",
    "from tkinter import messagebox\n",
    "\n",
    "top = tk.Tk()\n",
    "top.title(\"Currency Calculator\")\n",
    "top.geometry(\"700x700\")\n",
    "top.configure(bg = \"cornsilk\")\n",
    "inr = tk.IntVar()\n",
    "#i  = tk.PhotoImage(file = \"\")\n",
    "#bg = tk.Label(top,image = i)\n",
    "#bg.place(relwidth=1, relheight=1)\n",
    "\n",
    "def usd():\n",
    "    a = inr.get()\n",
    "    u = a/83\n",
    "    messagebox.showinfo(\"converter\",\"USD = %i\" %u )\n",
    "def eur():\n",
    "    a = inr.get()\n",
    "    e = a/89\n",
    "    messagebox.showinfo(\"converter\",\"EUR = %i\" %e )\n",
    "def pound():\n",
    "    a = inr.get()\n",
    "    p = a/105\n",
    "    messagebox.showinfo(\"converter\",\"POUND = %i\" %p )\n",
    "def dinar():\n",
    "    a = inr.get()\n",
    "    d = a/272\n",
    "    messagebox.showinfo(\"converter\",\"DINAR = %i\" %d )\n",
    "l = tk.Label(top,text = \"Enter your Amount in INR \",font = \"khand\", bg = \"snow3\").place(x = 250, y = 150)\n",
    "e = tk.Entry(top, textvariable = inr,width = 30).place(x = 270, y = 190)\n",
    "b1 = tk.Button(top,text = \"USD\",width = 20,bg = \"NavajoWhite3\",command = usd).place(x = 290, y = 220)\n",
    "b2 = tk.Button(top,text = \"EUR\",width = 20,bg = \"NavajoWhite3\",command = eur).place(x = 290, y = 250)\n",
    "b3 = tk.Button(top,text = \"POUND\",width = 20,bg = \"NavajoWhite3\",command = pound).place(x = 290, y = 280)\n",
    "b4 = tk.Button(top,text = \"DINAR\",width = 20,bg = \"NavajoWhite3\",command = dinar).place(x = 290, y = 310)\n",
    "top.mainloop()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f4da4b89-1689-4b44-883e-7b11dad1862e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.11.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}