sms-spam-classifier.ipynb

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   "source": [
    "<h1 style=\"color:skyblue;font-weight:700;font-size:3rem;\">SMS Spam Classifier</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Importing Libraries\n",
    "Importing the necessary libraries and downloading the required corpora"
   ]
  },
  {
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   "source": [
    "import re\n",
    "import pickle\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "import nltk\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem import WordNetLemmatizer\n",
    "from nltk import word_tokenize, sent_tokenize\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "\n",
    "from sklearn.model_selection import train_test_split as tts\n",
    "from sklearn.model_selection import cross_val_score as cv_score\n",
    "\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Downloading the `wordnet` corpora"
   ]
  },
  {
   "cell_type": "code",
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   "metadata": {
    "execution": {
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   "source": [
    "nltk.download('wordnet')"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading Data"
   ]
  },
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   "execution_count": 3,
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       "  <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",
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       "  </tbody>\n",
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      "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",
       "  Unnamed: 3 Unnamed: 4  \n",
       "0        NaN        NaN  \n",
       "1        NaN        NaN  \n",
       "2        NaN        NaN  \n",
       "3        NaN        NaN  \n",
       "4        NaN        NaN  "
      ]
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     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "df = pd.read_csv(r'spam.csv', encoding=\"iso-8859-1\")\n",
    "df.head()"
   ]
  },
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     "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": [
    "df.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This dataset contains `5572` text messages in **English** that have been classified as either **ham** or **spam**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modifying the columns\n",
    "* **Dropping** the redundant unnecessary columns\n",
    "* **Renaming** the `v1` and `v2` columns to `label` and `sms`"
   ]
  },
  {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>label</th>\n",
       "      <th>sms</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",
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      "text/plain": [
       "  label                                                sms\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..."
      ]
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   "source": [
    "df.drop(df.columns[2:].values, axis=1, inplace=True)\n",
    "df.rename(columns={\"v1\": \"label\", \"v2\": \"sms\"}, inplace=True)\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploratory Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data exploration\n",
    "Checking whether or not the dataset is **imbalanced** based on count of labels"
   ]
  },
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   "execution_count": 6,
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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use(plt.style.available[12])\n",
    "\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "fig = sns.countplot(x=df['label'], palette=sns.color_palette('colorblind'))\n",
    "\n",
    "fig.set_title(\"Distribution of Classes\", fontdict={'fontsize':16, 'fontweight':'bold'}, pad=10)\n",
    "for container in fig.containers:\n",
    "    fig.bar_label(container, label_type='edge', color='#fff', padding=-15)\n",
    "\n",
    "fig.set_ylabel(\"Number of messages\", labelpad=12, fontsize=10)\n",
    "fig.set_xlabel(\"Labels\", labelpad=8, fontsize=10, fontweight='bold')\n",
    "fig.set_xticks([0, 1], [\"Ham\", \"Spam\"])\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Observation :** The imbalance in the dataset is quite evident, with over `4825` **Ham** but only `747` **Spam** messages."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Feature engineering\n",
    "Creating the following features for EDA :\n",
    "1. `n_characters` - Number of characters in a message\n",
    "2. `n_sentences` - Number of sentences in a message\n",
    "3. `n_words` - Number of words in a sentence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:40.268827Z",
     "iopub.status.busy": "2024-10-26T10:15:40.268374Z",
     "iopub.status.idle": "2024-10-26T10:15:42.698304Z",
     "shell.execute_reply": "2024-10-26T10:15:42.696890Z",
     "shell.execute_reply.started": "2024-10-26T10:15:40.268779Z"
    },
    "trusted": true
   },
   "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>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>n_characters</th>\n",
       "      <td>5572.0</td>\n",
       "      <td>80.118808</td>\n",
       "      <td>59.690841</td>\n",
       "      <td>2.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>910.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>n_sentences</th>\n",
       "      <td>5572.0</td>\n",
       "      <td>1.996411</td>\n",
       "      <td>1.520159</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.5</td>\n",
       "      <td>2.0</td>\n",
       "      <td>38.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>n_words</th>\n",
       "      <td>5572.0</td>\n",
       "      <td>18.699390</td>\n",
       "      <td>13.741932</td>\n",
       "      <td>1.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>220.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               count       mean        std  min   25%   50%    75%    max\n",
       "n_characters  5572.0  80.118808  59.690841  2.0  36.0  61.0  121.0  910.0\n",
       "n_sentences   5572.0   1.996411   1.520159  1.0   1.0   1.5    2.0   38.0\n",
       "n_words       5572.0  18.699390  13.741932  1.0   9.0  15.0   27.0  220.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['n_characters'] = df.sms.apply(len)\n",
    "df['n_sentences'] = df.sms.apply(lambda row: sent_tokenize(row)).apply(len)\n",
    "df['n_words'] = df.sms.apply(lambda row: word_tokenize(row)).apply(len)\n",
    "\n",
    "df.describe().T"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Detecting outliers\n",
    "Finding out the outliers in the dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### PAIRPLOT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:42.702890Z",
     "iopub.status.busy": "2024-10-26T10:15:42.702486Z",
     "iopub.status.idle": "2024-10-26T10:15:48.777697Z",
     "shell.execute_reply": "2024-10-26T10:15:48.776281Z",
     "shell.execute_reply.started": "2024-10-26T10:15:42.702853Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 838.125x750 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data=df, hue='label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A lot of outliers are observable under the **ham** class in the above plot."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### BOXPLOT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:29:52.665742Z",
     "iopub.status.busy": "2024-10-26T10:29:52.665169Z",
     "iopub.status.idle": "2024-10-26T10:29:53.106879Z",
     "shell.execute_reply": "2024-10-26T10:29:53.105525Z",
     "shell.execute_reply.started": "2024-10-26T10:29:52.665688Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(2, 1, figsize=(8, 6), sharex=False)\n",
    "fig.suptitle(\"Boxplots for tokens\", size=16, weight='bold')\n",
    "\n",
    "sns.boxplot(x='n_characters', data=df, palette=sns.color_palette('Paired'), ax=ax[0])\n",
    "ax[0].set_xlabel(\"Number of characters\", size=10, labelpad=10, fontweight='bold')\n",
    "ax[0].set_yticks([])\n",
    "ax[0].set_xticks([i for i in range(0, 950, 50)])\n",
    "\n",
    "sns.boxplot(x='n_words', data=df, palette=sns.color_palette('Set2'), ax=ax[1])\n",
    "ax[1].set_xlabel(\"Number of words\", size=10, labelpad=10, fontweight='bold')\n",
    "ax[1].set_yticks([])\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The outliers can be dropped by capping the values of the `n_characters` column at `300` or `250`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dropping outliers\n",
    "Capping the `n_characters` column at `250` characters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:49.168743Z",
     "iopub.status.busy": "2024-10-26T10:15:49.168106Z",
     "iopub.status.idle": "2024-10-26T10:15:49.200963Z",
     "shell.execute_reply": "2024-10-26T10:15:49.199181Z",
     "shell.execute_reply.started": "2024-10-26T10:15:49.168676Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 5504 entries, 0 to 5571\n",
      "Data columns (total 5 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   label         5504 non-null   object\n",
      " 1   sms           5504 non-null   object\n",
      " 2   n_characters  5504 non-null   int64 \n",
      " 3   n_sentences   5504 non-null   int64 \n",
      " 4   n_words       5504 non-null   int64 \n",
      "dtypes: int64(3), object(2)\n",
      "memory usage: 258.0+ KB\n"
     ]
    }
   ],
   "source": [
    "data = df[df.n_characters < 250]\n",
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, there are `5504` messages left in the dataset."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### PAIRPLOT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:49.203086Z",
     "iopub.status.busy": "2024-10-26T10:15:49.202678Z",
     "iopub.status.idle": "2024-10-26T10:15:55.014454Z",
     "shell.execute_reply": "2024-10-26T10:15:55.012848Z",
     "shell.execute_reply.started": "2024-10-26T10:15:49.203047Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 838.125x750 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(data, hue='label')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data cleaning\n",
    "- **Replacing** all the non-alphanumeric characters with spaces\n",
    "- **Converting** all the characters to `lowercase`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:55.016461Z",
     "iopub.status.busy": "2024-10-26T10:15:55.016072Z",
     "iopub.status.idle": "2024-10-26T10:15:55.162582Z",
     "shell.execute_reply": "2024-10-26T10:15:55.161169Z",
     "shell.execute_reply.started": "2024-10-26T10:15:55.016421Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "go until jurong point crazy available only in bugis n great world la e buffet cine there got amore wat\n",
      "ok lar joking wif u oni\n",
      "free entry in a wkly comp to win fa cup final tkts st may text fa to to receive entry question std txt rate t c s apply over s\n",
      "u dun say so early hor u c already then say\n",
      "nah i don t think he goes to usf he lives around here though\n"
     ]
    }
   ],
   "source": [
    "def clean_sms(sms: str) -> str:\n",
    "    x = re.sub(r'[^a-zA-Z]', ' ', sms).strip()\n",
    "    x = map(lambda word: word.strip().lower(), x.split(' '))\n",
    "    cleaned_sms = ' '.join([word for word in x if word != ''])\n",
    "    return cleaned_sms\n",
    "\n",
    "data.sms = data.sms.apply(clean_sms)\n",
    "for sms in data.sms.head().values:\n",
    "    print(sms)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Tokenization**\n",
    "Tokenizing the **words** in each of the `sms` entries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:55.164908Z",
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     "shell.execute_reply.started": "2024-10-26T10:15:55.164864Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['go', 'until', 'jurong', 'point', 'crazy', 'available', 'only', 'in', 'bugis', 'n', 'great', 'world', 'la', 'e', 'buffet', 'cine', 'there', 'got', 'amore', 'wat']\n",
      "\n",
      "['ok', 'lar', 'joking', 'wif', 'u', 'oni']\n",
      "\n",
      "['free', 'entry', 'in', 'a', 'wkly', 'comp', 'to', 'win', 'fa', 'cup', 'final', 'tkts', 'st', 'may', 'text', 'fa', 'to', 'to', 'receive', 'entry', 'question', 'std', 'txt', 'rate', 't', 'c', 's', 'apply', 'over', 's']\n",
      "\n",
      "['u', 'dun', 'say', 'so', 'early', 'hor', 'u', 'c', 'already', 'then', 'say']\n",
      "\n",
      "['nah', 'i', 'don', 't', 'think', 'he', 'goes', 'to', 'usf', 'he', 'lives', 'around', 'here', 'though']\n",
      "\n"
     ]
    }
   ],
   "source": [
    "data['tokenized_sms'] = data.sms.apply(lambda row: word_tokenize(row))\n",
    "\n",
    "for t_sms in data.tokenized_sms.head().values:\n",
    "    print(t_sms, end='\\n\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Stopword** removal\n",
    "Removing the default **stopwords** from the `tokenized_sms` values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:56.305074Z",
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     "iopub.status.idle": "2024-10-26T10:15:56.341444Z",
     "shell.execute_reply": "2024-10-26T10:15:56.339827Z",
     "shell.execute_reply.started": "2024-10-26T10:15:56.305021Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SMS : \"go until jurong point crazy available only in bugis n great world la e buffet cine there got amore wat\"\n",
      "\n",
      "Tokenized SMS length\t: 20\n",
      "Non-stopword SMS length\t: 16\n"
     ]
    }
   ],
   "source": [
    "stops = set(stopwords.words(\"english\"))\n",
    "data['non_stop_sms'] = data.tokenized_sms.apply(lambda row: [word for word in row if word not in stops])\n",
    "\n",
    "print(f'SMS : \"{data.sms.loc[0]}\"\\n\\nTokenized SMS length\\t: {len(data.tokenized_sms.loc[0])}\\nNon-stopword SMS length\\t: {len(data.non_stop_sms.loc[0])}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Lemmatization**\n",
    "Extracting the root word or **lemma** from each word based on `v` POS tag i.e. **verbal** part of speech"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:56.343818Z",
     "iopub.status.busy": "2024-10-26T10:15:56.343368Z",
     "iopub.status.idle": "2024-10-26T10:15:56.766144Z",
     "shell.execute_reply": "2024-10-26T10:15:56.764716Z",
     "shell.execute_reply.started": "2024-10-26T10:15:56.343775Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['go', 'jurong', 'point', 'crazy', 'available', 'bugis', 'n', 'great', 'world', 'la', 'e', 'buffet', 'cine', 'get', 'amore', 'wat']\n",
      "\n",
      "['ok', 'lar', 'joke', 'wif', 'u', 'oni']\n",
      "\n",
      "['free', 'entry', 'wkly', 'comp', 'win', 'fa', 'cup', 'final', 'tkts', 'st', 'may', 'text', 'fa', 'receive', 'entry', 'question', 'std', 'txt', 'rate', 'c', 'apply']\n",
      "\n",
      "['u', 'dun', 'say', 'early', 'hor', 'u', 'c', 'already', 'say']\n",
      "\n",
      "['nah', 'think', 'go', 'usf', 'live', 'around', 'though']\n",
      "\n"
     ]
    }
   ],
   "source": [
    "lemmatizer = WordNetLemmatizer()\n",
    "\n",
    "def lemmatize_sms(words: pd.Series) -> list[str]:\n",
    "    lemmas = [lemmatizer.lemmatize(word, pos='v') for word in words]\n",
    "    return lemmas\n",
    "\n",
    "data['lemma_sms'] = data['non_stop_sms'].apply(lemmatize_sms)\n",
    "\n",
    "for l_sms in data.lemma_sms.head().values:\n",
    "    print(l_sms, end='\\n\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## **Vectorization**\n",
    "Converting the words into **vectors** for transforming the data into a **numerical** format using the **TF-IDF** method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Building the **corpus** \n",
    "Building a corpus from the **lemmatized** text messages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:56.768450Z",
     "iopub.status.busy": "2024-10-26T10:15:56.767832Z",
     "iopub.status.idle": "2024-10-26T10:15:56.792071Z",
     "shell.execute_reply": "2024-10-26T10:15:56.790135Z",
     "shell.execute_reply.started": "2024-10-26T10:15:56.768355Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    go jurong point crazy available bugis n great ...\n",
       "1                                ok lar joke wif u oni\n",
       "2    free entry wkly comp win fa cup final tkts st ...\n",
       "3                  u dun say early hor u c already say\n",
       "4                  nah think go usf live around though\n",
       "Name: lemma_sms, dtype: object"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corpus = data['lemma_sms'].apply(lambda row: ' '.join(row))\n",
    "\n",
    "corpus[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Applying **vectorization**\n",
    "Obtaining the **feature vectors** from the corpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:56.795069Z",
     "iopub.status.busy": "2024-10-26T10:15:56.794573Z",
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     "shell.execute_reply.started": "2024-10-26T10:15:56.795026Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5504, 6333)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vectorizer = TfidfVectorizer()\n",
    "X = vectorizer.fit_transform(corpus).toarray()\n",
    "\n",
    "X.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Encoding **labels**\n",
    "Applying `LabelEncoder` to the message labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:57.124857Z",
     "iopub.status.busy": "2024-10-26T10:15:57.124405Z",
     "iopub.status.idle": "2024-10-26T10:15:57.139307Z",
     "shell.execute_reply": "2024-10-26T10:15:57.137947Z",
     "shell.execute_reply.started": "2024-10-26T10:15:57.124815Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0\n",
       "1    0\n",
       "2    1\n",
       "3    0\n",
       "4    0\n",
       "Name: label, dtype: int32"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "encoder = LabelEncoder()\n",
    "data.label = encoder.fit_transform(data.label)\n",
    "\n",
    "data.label.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Training"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Target and features\n",
    "Splitting up the **target** and the **features** from the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:57.141283Z",
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     "shell.execute_reply.started": "2024-10-26T10:15:57.141234Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((4403, 6333), (1101, 6333))"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = data.label\n",
    "X_train, X_test, y_train, y_test = tts(X, y, test_size=0.2, random_state=33)\n",
    "\n",
    "X_train.shape, X_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model pipeline\n",
    "Fitting the **training** data on a pipeline of models and obtaining their **cross-validation** scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:15:57.357986Z",
     "iopub.status.busy": "2024-10-26T10:15:57.357244Z",
     "iopub.status.idle": "2024-10-26T10:18:09.397114Z",
     "shell.execute_reply": "2024-10-26T10:18:09.395749Z",
     "shell.execute_reply.started": "2024-10-26T10:15:57.357754Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Cross-validation scores - Mean accuracy\n",
      "\n",
      "Gaussian Naive Bayes : 86.17%\n",
      "Logistic Regression : 95.71%\n",
      "Decision Tree Classifier : 95.82%\n",
      "Random Forest Classifier : 97.68%\n"
     ]
    }
   ],
   "source": [
    "pipeline = {\n",
    "    'Gaussian Naive Bayes': GaussianNB(),\n",
    "    'Logistic Regression': LogisticRegression(warm_start=True, max_iter=200, n_jobs=-1),\n",
    "    'Decision Tree Classifier': DecisionTreeClassifier(max_depth=20, max_leaf_nodes=100),\n",
    "    'Random Forest Classifier': RandomForestClassifier(warm_start=True, n_estimators=35, n_jobs=-1)\n",
    "}\n",
    "\n",
    "print(\"Cross-validation scores - Mean accuracy\\n\")\n",
    "\n",
    "for name, model in pipeline.items():\n",
    "    model.fit(X_train, y_train)\n",
    "    score = cv_score(model, X_train, y_train, scoring='accuracy', cv=10)\n",
    "    print(f\"{name} : {(score.mean() * 100):.2f}%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `RandomForestClassifer` model gave the **highest** mean accuracy score on `10` folds of **training** data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Classification reports\n",
    "Evaluating the performance of the models on the **testing** dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T10:40:19.746092Z",
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     "shell.execute_reply": "2024-10-26T10:40:20.057000Z",
     "shell.execute_reply.started": "2024-10-26T10:40:19.746052Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gaussian Naive Bayes\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      0.87      0.92       952\n",
      "           1       0.53      0.91      0.67       149\n",
      "\n",
      "    accuracy                           0.88      1101\n",
      "   macro avg       0.76      0.89      0.80      1101\n",
      "weighted avg       0.92      0.88      0.89      1101\n",
      "\n",
      "Accuracy score : 87.74%\n",
      "\n",
      "\n",
      "Logistic Regression\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.96      1.00      0.98       952\n",
      "           1       0.99      0.75      0.85       149\n",
      "\n",
      "    accuracy                           0.97      1101\n",
      "   macro avg       0.98      0.88      0.92      1101\n",
      "weighted avg       0.97      0.97      0.96      1101\n",
      "\n",
      "Accuracy score : 96.55%\n",
      "\n",
      "\n",
      "Decision Tree Classifier\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.99      0.98       952\n",
      "           1       0.93      0.83      0.88       149\n",
      "\n",
      "    accuracy                           0.97      1101\n",
      "   macro avg       0.95      0.91      0.93      1101\n",
      "weighted avg       0.97      0.97      0.97      1101\n",
      "\n",
      "Accuracy score : 96.91%\n",
      "\n",
      "\n",
      "Random Forest Classifier\n",
      "\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.98      1.00      0.99       952\n",
      "           1       0.99      0.84      0.91       149\n",
      "\n",
      "    accuracy                           0.98      1101\n",
      "   macro avg       0.98      0.92      0.95      1101\n",
      "weighted avg       0.98      0.98      0.98      1101\n",
      "\n",
      "Accuracy score : 97.73%\n",
      "\n"
     ]
    }
   ],
   "source": [
    "preds = {}\n",
    "labels=['Ham', 'Spam']\n",
    "\n",
    "def report(*args):\n",
    "    print(f\"{args[0]}\\n\")\n",
    "    y_pred = args[1].predict(X_test)\n",
    "    preds.update({args[0] : y_pred})\n",
    "    \n",
    "    print(classification_report(y_test.astype('int'), y_pred))\n",
    "    print(f\"Accuracy score : {(accuracy_score(y_test.astype('int'), y_pred) * 100):.2f}%\", end='\\n\\n')\n",
    "\n",
    "for i, item in enumerate(pipeline.items()):\n",
    "    report(*item)\n",
    "    if i != len(pipeline) - 1:\n",
    "        print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Result**\n",
    "From the classification reports, it is clear that `RandomForestClassifier` offers the **highest** accuracy (~**98**%) on the testing data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Confusion matrices\n",
    "Plotting the **confusion matrix** for each model's prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "execution": {
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   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(2, 2, figsize=(10, 10))\n",
    "fig.text(0.5, 0.05, 'Predicted Labels', ha='center', fontsize=14)\n",
    "fig.text(0.05, 0.5, 'True Labels', va='center', rotation='vertical', fontsize=14)\n",
    "\n",
    "for ax, (name, model) in zip(axs.flatten(), pipeline.items()):\n",
    "    cm = confusion_matrix(y_test, preds[name])\n",
    "    sns.heatmap(cm, annot=True, fmt='d', ax=ax, cbar=False, cmap=sns.color_palette('colorblind', as_cmap=True) if name == 'Random Forest Classifier' else 'Blues')\n",
    "    \n",
    "    ax.set_title(f\"{name}\", pad=12, fontweight='bold' if name == 'Random Forest Classifier' else 'light', fontsize=12)\n",
    "    ax.set_xticklabels(labels)\n",
    "    ax.set_yticklabels(labels)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pickling\n",
    "Pickling the **vectorizer** and the `RandomForestClassifier` model in `.pkl` format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T11:42:13.272374Z",
     "iopub.status.busy": "2024-10-26T11:42:13.271812Z",
     "iopub.status.idle": "2024-10-26T11:42:13.292221Z",
     "shell.execute_reply": "2024-10-26T11:42:13.290810Z",
     "shell.execute_reply.started": "2024-10-26T11:42:13.272320Z"
    },
    "trusted": true
   },
   "outputs": [],
   "source": [
    "model_filename = r'rfc-model.pkl'\n",
    "vectorizer_filename = r'tfidf-vectorizer.pkl'\n",
    "\n",
    "pickle.dump(pipeline['Random Forest Classifier'], open(model_filename, 'wb'))\n",
    "pickle.dump(vectorizer, open(vectorizer_filename, 'wb'))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testing\n",
    "Testing the pickled model on **sample** spam message"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T11:43:05.012934Z",
     "iopub.status.busy": "2024-10-26T11:43:05.012493Z",
     "iopub.status.idle": "2024-10-26T11:43:05.030069Z",
     "shell.execute_reply": "2024-10-26T11:43:05.028510Z",
     "shell.execute_reply.started": "2024-10-26T11:43:05.012894Z"
    },
    "trusted": true
   },
   "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>RandomForestClassifier(n_estimators=35, n_jobs=-1, warm_start=True)</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;RandomForestClassifier<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.ensemble.RandomForestClassifier.html\">?<span>Documentation for RandomForestClassifier</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>RandomForestClassifier(n_estimators=35, n_jobs=-1, warm_start=True)</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "RandomForestClassifier(n_estimators=35, n_jobs=-1, warm_start=True)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loaded_model = pickle.load(open(model_filename, 'rb'))\n",
    "loaded_vectorizer = pickle.load(open(vectorizer_filename, 'rb'))\n",
    "\n",
    "loaded_model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T12:12:00.982354Z",
     "iopub.status.busy": "2024-10-26T12:12:00.981810Z",
     "iopub.status.idle": "2024-10-26T12:12:01.009084Z",
     "shell.execute_reply": "2024-10-26T12:12:01.007632Z",
     "shell.execute_reply.started": "2024-10-26T12:12:00.982303Z"
    },
    "trusted": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "SMS message\t:  \"Want to win $5,000 in this summer’s treasure hunt? Text “YES” to 4555 to reserve your ticket.T&Cs apply. \"\n",
      "True label\t:  SPAM\n",
      "Predicted label\t:  SPAM\n",
      "\n"
     ]
    }
   ],
   "source": [
    "sample = \"Want to win $5,000 in this summer’s treasure hunt? Text “YES” to 4555 to reserve your ticket.T&Cs apply.\"\n",
    "\n",
    "vector = loaded_vectorizer.transform([sample]).toarray()\n",
    "pred_label = \"HAM\" if loaded_model.predict(vector.reshape(1, -1))[0] == 0 else \"SPAM\"\n",
    "\n",
    "print(f\"\"\"\n",
    "SMS message\\t: \"{sample}\"\n",
    "True label\\t: SPAM\n",
    "Predicted label\\t: {pred_label}\n",
    "\"\"\")"
   ]
  }
 ],
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