Task # 4 - CodSoft - Internship.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "fedd6a27",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e42791ab",
   "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>v1</th>\n",
       "      <th>v2</th>\n",
       "      <th>Unnamed: 2</th>\n",
       "      <th>Unnamed: 3</th>\n",
       "      <th>Unnamed: 4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ì_ b going to esplanade fr home?</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5572 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        v1                                                 v2 Unnamed: 2  \\\n",
       "0      ham  Go until jurong point, crazy.. Available only ...        NaN   \n",
       "1      ham                      Ok lar... Joking wif u oni...        NaN   \n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...        NaN   \n",
       "3      ham  U dun say so early hor... U c already then say...        NaN   \n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...        NaN   \n",
       "...    ...                                                ...        ...   \n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...        NaN   \n",
       "5568   ham              Will Ì_ b going to esplanade fr home?        NaN   \n",
       "5569   ham  Pity, * was in mood for that. So...any other s...        NaN   \n",
       "5570   ham  The guy did some bitching but I acted like i'd...        NaN   \n",
       "5571   ham                         Rofl. Its true to its name        NaN   \n",
       "\n",
       "     Unnamed: 3 Unnamed: 4  \n",
       "0           NaN        NaN  \n",
       "1           NaN        NaN  \n",
       "2           NaN        NaN  \n",
       "3           NaN        NaN  \n",
       "4           NaN        NaN  \n",
       "...         ...        ...  \n",
       "5567        NaN        NaN  \n",
       "5568        NaN        NaN  \n",
       "5569        NaN        NaN  \n",
       "5570        NaN        NaN  \n",
       "5571        NaN        NaN  \n",
       "\n",
       "[5572 rows x 5 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# load data\n",
    "df = pd.read_csv('spam.csv', encoding='latin-1')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ff787dae",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5572 entries, 0 to 5571\n",
      "Data columns (total 5 columns):\n",
      " #   Column      Non-Null Count  Dtype \n",
      "---  ------      --------------  ----- \n",
      " 0   v1          5572 non-null   object\n",
      " 1   v2          5572 non-null   object\n",
      " 2   Unnamed: 2  50 non-null     object\n",
      " 3   Unnamed: 3  12 non-null     object\n",
      " 4   Unnamed: 4  6 non-null      object\n",
      "dtypes: object(5)\n",
      "memory usage: 217.8+ KB\n"
     ]
    }
   ],
   "source": [
    "# data info\n",
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "391308c0",
   "metadata": {},
   "source": [
    "# Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e299ab67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "v1               0\n",
       "v2               0\n",
       "Unnamed: 2    5522\n",
       "Unnamed: 3    5560\n",
       "Unnamed: 4    5566\n",
       "dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# chek null or empty values in the data\n",
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "49ef490f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop irrelevant columns\n",
    "df.drop(['Unnamed: 2','Unnamed: 3','Unnamed: 4'],axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9b8a4a7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .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>v1</th>\n",
       "      <th>v2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ì_ b going to esplanade fr home?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5572 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        v1                                                 v2\n",
       "0      ham  Go until jurong point, crazy.. Available only ...\n",
       "1      ham                      Ok lar... Joking wif u oni...\n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3      ham  U dun say so early hor... U c already then say...\n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...\n",
       "...    ...                                                ...\n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...\n",
       "5568   ham              Will Ì_ b going to esplanade fr home?\n",
       "5569   ham  Pity, * was in mood for that. So...any other s...\n",
       "5570   ham  The guy did some bitching but I acted like i'd...\n",
       "5571   ham                         Rofl. Its true to its name\n",
       "\n",
       "[5572 rows x 2 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# original data\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1f34f23c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "v1    0\n",
       "v2    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# chek null valus\n",
    "\n",
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0a655c7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 5572 entries, 0 to 5571\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype \n",
      "---  ------  --------------  ----- \n",
      " 0   v1      5572 non-null   object\n",
      " 1   v2      5572 non-null   object\n",
      "dtypes: object(2)\n",
      "memory usage: 87.2+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a20664f4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5572, 2)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# chek shape of the data\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "19270066",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "403"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# chek duplicated rows\n",
    "\n",
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "32c2e120",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop_duplicates(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "9895e186",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "d906c670",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>v1</th>\n",
       "      <th>v2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ham</td>\n",
       "      <td>Go until jurong point, crazy.. Available only ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ham</td>\n",
       "      <td>Ok lar... Joking wif u oni...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>spam</td>\n",
       "      <td>Free entry in 2 a wkly comp to win FA Cup fina...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ham</td>\n",
       "      <td>U dun say so early hor... U c already then say...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ham</td>\n",
       "      <td>Nah I don't think he goes to usf, he lives aro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5567</th>\n",
       "      <td>spam</td>\n",
       "      <td>This is the 2nd time we have tried 2 contact u...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5568</th>\n",
       "      <td>ham</td>\n",
       "      <td>Will Ì_ b going to esplanade fr home?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5569</th>\n",
       "      <td>ham</td>\n",
       "      <td>Pity, * was in mood for that. So...any other s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5570</th>\n",
       "      <td>ham</td>\n",
       "      <td>The guy did some bitching but I acted like i'd...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5571</th>\n",
       "      <td>ham</td>\n",
       "      <td>Rofl. Its true to its name</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5169 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        v1                                                 v2\n",
       "0      ham  Go until jurong point, crazy.. Available only ...\n",
       "1      ham                      Ok lar... Joking wif u oni...\n",
       "2     spam  Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3      ham  U dun say so early hor... U c already then say...\n",
       "4      ham  Nah I don't think he goes to usf, he lives aro...\n",
       "...    ...                                                ...\n",
       "5567  spam  This is the 2nd time we have tried 2 contact u...\n",
       "5568   ham              Will Ì_ b going to esplanade fr home?\n",
       "5569   ham  Pity, * was in mood for that. So...any other s...\n",
       "5570   ham  The guy did some bitching but I acted like i'd...\n",
       "5571   ham                         Rofl. Its true to its name\n",
       "\n",
       "[5169 rows x 2 columns]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "aced2742",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={'v1':'target','v2':'text_messages'}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5fc57785",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "target           0\n",
       "text_messages    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isna().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "49ea7e6c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.duplicated().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2738d97a",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = df['text_messages']\n",
    "y = df['target']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "0f333f13",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0\n",
       "1       0\n",
       "2       1\n",
       "3       0\n",
       "4       0\n",
       "       ..\n",
       "5567    1\n",
       "5568    0\n",
       "5569    0\n",
       "5570    0\n",
       "5571    0\n",
       "Name: target, Length: 5169, dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# label encoding the target varibale\n",
    "\n",
    "y = y.apply(lambda x: 1 if x=='spam' else 0)\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "f4b639a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "x_train, x_test, y_train, y_test = train_test_split(x,y, test_size=0.20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "ec0e1d81",
   "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>Pipeline(steps=[(&#x27;preprocessing&#x27;, CountVectorizer()), (&#x27;NB&#x27;, MultinomialNB())])</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></label><div class=\"sk-toggleable__content \"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;, CountVectorizer()), (&#x27;NB&#x27;, MultinomialNB())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;CountVectorizer<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html\">?<span>Documentation for CountVectorizer</span></a></label><div class=\"sk-toggleable__content \"><pre>CountVectorizer()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label  sk-toggleable__label-arrow \">&nbsp;MultinomialNB<a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.naive_bayes.MultinomialNB.html\">?<span>Documentation for MultinomialNB</span></a></label><div class=\"sk-toggleable__content \"><pre>MultinomialNB()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('preprocessing', CountVectorizer()), ('NB', MultinomialNB())])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "\n",
    "pipeline = Pipeline([('preprocessing',CountVectorizer()),('NB',MultinomialNB())])\n",
    "pipeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ad0645f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\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-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 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-2 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-2 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-2 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-2 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-2 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-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 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-2 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-2 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-2 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-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 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-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 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-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 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-2 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-2 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-2 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-2 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-2 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-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 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-2 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-2 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-2 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-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 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-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 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-2 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-2 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-2 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-2 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-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;, CountVectorizer()), (&#x27;NB&#x27;, MultinomialNB())])</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 sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;Pipeline<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>Pipeline(steps=[(&#x27;preprocessing&#x27;, CountVectorizer()), (&#x27;NB&#x27;, MultinomialNB())])</pre></div> </div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;CountVectorizer<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html\">?<span>Documentation for CountVectorizer</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>CountVectorizer()</pre></div> </div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;MultinomialNB<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.naive_bayes.MultinomialNB.html\">?<span>Documentation for MultinomialNB</span></a></label><div class=\"sk-toggleable__content fitted\"><pre>MultinomialNB()</pre></div> </div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('preprocessing', CountVectorizer()), ('NB', MultinomialNB())])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline.fit(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6ae514c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9939540507859734"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Model training score\n",
    "\n",
    "pipeline.score(x_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b99c5c8c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9748549323017408"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Model Testing Score\n",
    "\n",
    "pipeline.score(x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "5ca920f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 0, 0, ..., 0, 1, 0], dtype=int64)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Model prediction\n",
    "\n",
    "pipeline_prediction = pipeline.predict(x_test)\n",
    "pipeline_prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "59e0a8a2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "365     0\n",
       "1025    0\n",
       "2467    0\n",
       "3681    0\n",
       "177     0\n",
       "       ..\n",
       "4420    0\n",
       "4492    0\n",
       "4833    0\n",
       "2296    1\n",
       "2671    0\n",
       "Name: target, Length: 1034, dtype: int64"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "8de42cc0",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import classification_report, confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "9c5fcb63",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'              precision    recall  f1-score   support\\n\\n           0       1.00      0.97      0.99       925\\n           1       0.82      0.98      0.89       109\\n\\n    accuracy                           0.97      1034\\n   macro avg       0.91      0.98      0.94      1034\\nweighted avg       0.98      0.97      0.98      1034\\n'"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# classification Report\n",
    "\n",
    "classification_report(pipeline_prediction,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "ffa9d687",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[901,  24],\n",
       "       [  2, 107]], dtype=int64)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cm = confusion_matrix(pipeline_prediction,y_test)\n",
    "cm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "4b1195a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "sns.heatmap(cm, annot=True, fmt='d', cmap='coolwarm')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20ec2083",
   "metadata": {},
   "source": [
    "# Thank You :)"
   ]
  }
 ],
 "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": "3.11.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}