spam_mail_classification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "223bd408",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "from sklearn.linear_model import LogisticRegression \n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d850f137",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Message</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",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Category                                            Message\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..."
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"mail_data.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "745fae81",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method DataFrame.count of       Category  Message\n",
       "0        False    False\n",
       "1        False    False\n",
       "2        False    False\n",
       "3        False    False\n",
       "4        False    False\n",
       "...        ...      ...\n",
       "5567     False    False\n",
       "5568     False    False\n",
       "5569     False    False\n",
       "5570     False    False\n",
       "5571     False    False\n",
       "\n",
       "[5572 rows x 2 columns]>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().count"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4b259804",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Message</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 ü 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": [
       "     Category                                            Message\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 ü 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": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.fillna(\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d9a159f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5572, 2)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "raw",
   "id": "7b86743b",
   "metadata": {},
   "source": [
    "label encoding \n",
    "where spam=0 ; ham=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3227d50d",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df['Category']== 'spam' , 'Category']=0\n",
    "df.loc[df['Category']== 'ham' , 'Category']=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "75c39da2",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = df[\"Message\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d87d4fbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "y= df[\"Category\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9bb57293",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       Go until jurong point, crazy.. Available only ...\n",
       "1                           Ok lar... Joking wif u oni...\n",
       "2       Free entry in 2 a wkly comp to win FA Cup fina...\n",
       "3       U dun say so early hor... U c already then say...\n",
       "4       Nah I don't think he goes to usf, he lives aro...\n",
       "                              ...                        \n",
       "5567    This is the 2nd time we have tried 2 contact u...\n",
       "5568                 Will ü b going to esplanade fr home?\n",
       "5569    Pity, * was in mood for that. So...any other s...\n",
       "5570    The guy did some bitching but I acted like i'd...\n",
       "5571                           Rofl. Its true to its name\n",
       "Name: Message, Length: 5572, dtype: object"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d571a41a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       1\n",
       "1       1\n",
       "2       0\n",
       "3       1\n",
       "4       1\n",
       "       ..\n",
       "5567    0\n",
       "5568    1\n",
       "5569    1\n",
       "5570    1\n",
       "5571    1\n",
       "Name: Category, Length: 5572, dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d5a51566",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test = train_test_split(x,y,test_size=0.2,random_state=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "66554626",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3075                  Don know. I did't msg him recently.\n",
       "1787    Do you know why god created gap between your f...\n",
       "1614                         Thnx dude. u guys out 2nite?\n",
       "4304                                      Yup i'm free...\n",
       "3266    44 7732584351, Do you want a New Nokia 3510i c...\n",
       "                              ...                        \n",
       "789     5 Free Top Polyphonic Tones call 087018728737,...\n",
       "968     What do u want when i come back?.a beautiful n...\n",
       "1667    Guess who spent all last night phasing in and ...\n",
       "3321    Eh sorry leh... I din c ur msg. Not sad alread...\n",
       "1688    Free Top ringtone -sub to weekly ringtone-get ...\n",
       "Name: Message, Length: 4457, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0bb0dd04",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3075    1\n",
       "1787    1\n",
       "1614    1\n",
       "4304    1\n",
       "3266    0\n",
       "       ..\n",
       "789     0\n",
       "968     1\n",
       "1667    1\n",
       "3321    1\n",
       "1688    0\n",
       "Name: Category, Length: 4457, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7dda4af",
   "metadata": {},
   "source": [
    "# feature extraction\n",
    "transform x data to feature vectors that can be used as input "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "d674e4dd",
   "metadata": {},
   "outputs": [],
   "source": [
    "f_e = TfidfVectorizer(min_df=1,stop_words='english',lowercase='True')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "984ee6cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train_f = f_e.fit_transform(x_train)\n",
    "x_test_f = f_e.transform(x_test)\n",
    "\n",
    "y_train = y_train.astype('int')\n",
    "y_test = y_test.astype('int')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "80cce37c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3075                  Don know. I did't msg him recently.\n",
       "1787    Do you know why god created gap between your f...\n",
       "1614                         Thnx dude. u guys out 2nite?\n",
       "4304                                      Yup i'm free...\n",
       "3266    44 7732584351, Do you want a New Nokia 3510i c...\n",
       "                              ...                        \n",
       "789     5 Free Top Polyphonic Tones call 087018728737,...\n",
       "968     What do u want when i come back?.a beautiful n...\n",
       "1667    Guess who spent all last night phasing in and ...\n",
       "3321    Eh sorry leh... I din c ur msg. Not sad alread...\n",
       "1688    Free Top ringtone -sub to weekly ringtone-get ...\n",
       "Name: Message, Length: 4457, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "229d6304",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<4457x7431 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 34775 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d30da97c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<1115x7431 sparse matrix of type '<class 'numpy.float64'>'\n",
       "\twith 7687 stored elements in Compressed Sparse Row format>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test_f"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4454c94c",
   "metadata": {},
   "outputs": [],
   "source": [
    "lr= LogisticRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1869d144",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LogisticRegression()"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lr.fit(x_train_f,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5424d7e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "predict = lr.predict(x_train_f)\n",
    "predict_test = lr.predict(x_test_f)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "158e537b",
   "metadata": {},
   "source": [
    "# accuracy score checking\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c8caeadf",
   "metadata": {},
   "outputs": [],
   "source": [
    "accuracy = accuracy_score(y_train,predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "bea1e329",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9670181736594121"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1a424a15",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9659192825112107"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "accuracy_score(y_test,predict_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0d8a4f3",
   "metadata": {},
   "source": [
    "# Building a predictive model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "24d3f2b7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Mail is Ham\n"
     ]
    }
   ],
   "source": [
    "input_mail = [\"I've been searching for the right words to thank you for this breather. I promise i wont take your help for granted and will fulfil my promise. You have been wonderful and a blessing at all times\"]\n",
    "input_trans = f_e.transform(input_mail)\n",
    "# prediction making \n",
    "x = lr.predict(input_trans)\n",
    "\n",
    "if x == 1:\n",
    "    print(' Mail is Ham')\n",
    "else:\n",
    "    print('Mail is spam')"
   ]
  }
 ],
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