Classifying Topic Label.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8fc66583-7185-4aa7-88da-7318b9eee5f7",
   "metadata": {},
   "source": [
    "## Install Library"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b4f89431-ad95-42a3-b438-8087910272c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\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.svm import SVC\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.metrics import classification_report, confusion_matrix\n",
    "from nltk.tokenize import word_tokenize\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem import PorterStemmer, WordNetLemmatizer\n",
    "from sklearn.svm import SVC\n",
    "import nltk\n",
    "from sklearn.metrics import accuracy_score\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "import seaborn as sns\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "import pandas as pd\n",
    "import re\n",
    "from nltk.corpus import stopwords\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fd996d16-4a2e-4119-81cc-051878891fec",
   "metadata": {},
   "source": [
    "## Read Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1c53f1db-5f65-4b87-b5cf-665da33411b3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define data path\n",
    "data_path = \"./bbc\"\n",
    "\n",
    "# Load data\n",
    "folders = os.listdir(data_path)\n",
    "documents = []\n",
    "\n",
    "for folder in os.listdir(data_path):\n",
    "    folder_dir = os.path.join(data_path, folder)\n",
    "    # Check if it's a directory\n",
    "    if os.path.isdir(folder_dir):\n",
    "        for file in os.listdir(folder_dir):\n",
    "            with open(os.path.join(folder_dir, file), 'r', encoding='latin-1') as f:\n",
    "                text = f.read()\n",
    "                documents.append({'before_preprocessing': text, 'category': folder})\n",
    "\n",
    "            \n",
    "bbc_data = pd.DataFrame(documents)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ba9aa811-cd90-40b3-9213-bd761d3010b1",
   "metadata": {
    "scrolled": 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>before_preprocessing</th>\n",
       "      <th>category</th>\n",
       "      <th>length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Musicians to tackle US red tape\\n\\nMusicians' ...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>2261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>U2's desire to be number one\\n\\nU2, who have w...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>4810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rocker Doherty in on-stage fight\\n\\nRock singe...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>2127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Snicket tops US box office chart\\n\\nThe film a...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>1046</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ocean's Twelve raids box office\\n\\nOcean's Twe...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>1586</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                before_preprocessing       category  length\n",
       "0  Musicians to tackle US red tape\\n\\nMusicians' ...  entertainment    2261\n",
       "1  U2's desire to be number one\\n\\nU2, who have w...  entertainment    4810\n",
       "2  Rocker Doherty in on-stage fight\\n\\nRock singe...  entertainment    2127\n",
       "3  Snicket tops US box office chart\\n\\nThe film a...  entertainment    1046\n",
       "4  Ocean's Twelve raids box office\\n\\nOcean's Twe...  entertainment    1586"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbc_data['length'] = bbc_data['before_preprocessing'].apply(lambda x: len(x))\n",
    "bbc_data.head()\n",
    "     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cc3e836d-d20b-4f6c-ae6d-817e15eeb84f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Category of the First Document: entertainment\n",
      "Length of the Text: 2261\n",
      "Full Text of the First Document:\n",
      "Musicians to tackle US red tape\n",
      "\n",
      "Musicians' groups are to tackle US visa regulations which are blamed for hindering British acts' chances of succeeding across the Atlantic.\n",
      "\n",
      "A singer hoping to perform in the US can expect to pay $1,300 (Â£680) simply for obtaining a visa. Groups including the Musicians' Union are calling for an end to the \"raw deal\" faced by British performers. US acts are not faced with comparable expense and bureaucracy when visiting the UK for promotional purposes.\n",
      "\n",
      "Nigel McCune from the Musicians' Union said British musicians are \"disadvantaged\" compared to their US counterparts. A sponsor has to make a petition on their behalf, which is a form amounting to nearly 30 pages, while musicians face tougher regulations than athletes and journalists. \"If you make a mistake on your form, you risk a five-year ban and thus the ability to further your career,\" says Mr McCune.\n",
      "\n",
      "\"The US is the world's biggest music market, which means something has to be done about the creaky bureaucracy,\" says Mr McCune. \"The current situation is preventing British acts from maintaining momentum and developing in the US,\" he added.\n",
      "\n",
      "The Musicians' Union stance is being endorsed by the Music Managers' Forum (MMF), who say British artists face \"an uphill struggle\" to succeed in the US, thanks to the tough visa requirements, which are also seen as impractical. The MMF's general secretary James Seller said: \"Imagine if you were an orchestra from the Orkneys? Every member would have to travel to London to have their visas processed.\"\n",
      "\n",
      "\"The US market is seen as the holy grail and one of the benchmarks of success, and we're still going to fight to get in there. \"It's still very important, but there are other markets like Europe, India and China,\" added Mr Seller. A Department for Media, Culture and Sport spokeswoman said: \"We're aware that people are experiencing problems, and are working with the US embassy and record industry to see what we can do about it.\" A US Embassy spokesman said: \"We are aware that entertainers require visas for time-specific visas and are doing everything we can to process those applications speedily.\" \"We are aware of the importance of cultural exchange and we will do our best to facilitate that,\" he added.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(\"Category of the First Document:\", bbc_data.iloc[0]['category'])  # Print the category of the first document\n",
    "print(\"Length of the Text:\", len(bbc_data.iloc[0]['before_preprocessing']))  # Print the length of the text in the first document\n",
    "print(\"Full Text of the First Document:\")\n",
    "print(bbc_data.iloc[0]['before_preprocessing'])  # Print the full text of the first document"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3848bd96-2c1c-4980-8800-26f1875f0f44",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "category\n",
       "sport            511\n",
       "business         510\n",
       "politics         417\n",
       "tech             401\n",
       "entertainment    386\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbc_data['category'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "98e958a3-2956-4f86-b35f-0ba192f4b2d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x600 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bbc_data[\"category\"].value_counts(ascending=True).plot.barh()\n",
    "plt.title(\"Frequency of Classes\")\n",
    "plt.figure(figsize=(10, 6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf8d48ec-2d84-40c4-8f89-7c3aa944834f",
   "metadata": {},
   "source": [
    "### Text Pre-Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "95b24318-43be-4215-80db-612d8d2427d2",
   "metadata": {},
   "outputs": [],
   "source": [
    "lemmatizer = WordNetLemmatizer()\n",
    "stop_words = set(stopwords.words('english'))\n",
    "\n",
    "def preprocess_document(doc):\n",
    "    doc = doc.lower()\n",
    "    doc = re.sub(r'\\d+', '', doc)\n",
    "    doc = re.sub(r'[^a-zA-Z\\s]', '', doc)\n",
    "    tokens = word_tokenize(doc)\n",
    "    lemmatized = [lemmatizer.lemmatize(token) for token in tokens if token not in stop_words]\n",
    "    preprocessed_doc = ' '.join(lemmatized)\n",
    "    return preprocessed_doc\n",
    "\n",
    "\n",
    "bbc_data['preprocessed'] = bbc_data['before_preprocessing'].apply(preprocess_document)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b6b0573a-c690-4c31-a2aa-af02193c5e1e",
   "metadata": {
    "scrolled": 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>before_preprocessing</th>\n",
       "      <th>category</th>\n",
       "      <th>length</th>\n",
       "      <th>preprocessed</th>\n",
       "      <th>length_after_cleaning</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Musicians to tackle US red tape\\n\\nMusicians' ...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>2261</td>\n",
       "      <td>musician tackle u red tape musician group tack...</td>\n",
       "      <td>1461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>U2's desire to be number one\\n\\nU2, who have w...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>4810</td>\n",
       "      <td>u desire number one u three prestigious grammy...</td>\n",
       "      <td>3027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Rocker Doherty in on-stage fight\\n\\nRock singe...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>2127</td>\n",
       "      <td>rocker doherty onstage fight rock singer pete ...</td>\n",
       "      <td>1420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Snicket tops US box office chart\\n\\nThe film a...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>1046</td>\n",
       "      <td>snicket top u box office chart film adaptation...</td>\n",
       "      <td>746</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ocean's Twelve raids box office\\n\\nOcean's Twe...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>1586</td>\n",
       "      <td>ocean twelve raid box office ocean twelve crim...</td>\n",
       "      <td>1130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>'Landmark movies' of 2004 hailed\\n\\nUS film pr...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>2121</td>\n",
       "      <td>landmark movie hailed u film professional decl...</td>\n",
       "      <td>1538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Pete Doherty misses bail deadline\\n\\nSinger Pe...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>1481</td>\n",
       "      <td>pete doherty miss bail deadline singer pete do...</td>\n",
       "      <td>1018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Fockers retain film chart crown\\n\\nComedy Meet...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>1821</td>\n",
       "      <td>fockers retain film chart crown comedy meet fo...</td>\n",
       "      <td>1139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Top gig award for Scissor Sisters\\n\\nNew York ...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>1238</td>\n",
       "      <td>top gig award scissor sister new york band sci...</td>\n",
       "      <td>854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Johnny Depp: The acting outlaw\\n\\nJohnny Depp,...</td>\n",
       "      <td>entertainment</td>\n",
       "      <td>3092</td>\n",
       "      <td>johnny depp acting outlaw johnny depp whose la...</td>\n",
       "      <td>2249</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                before_preprocessing       category  length  \\\n",
       "0  Musicians to tackle US red tape\\n\\nMusicians' ...  entertainment    2261   \n",
       "1  U2's desire to be number one\\n\\nU2, who have w...  entertainment    4810   \n",
       "2  Rocker Doherty in on-stage fight\\n\\nRock singe...  entertainment    2127   \n",
       "3  Snicket tops US box office chart\\n\\nThe film a...  entertainment    1046   \n",
       "4  Ocean's Twelve raids box office\\n\\nOcean's Twe...  entertainment    1586   \n",
       "5  'Landmark movies' of 2004 hailed\\n\\nUS film pr...  entertainment    2121   \n",
       "6  Pete Doherty misses bail deadline\\n\\nSinger Pe...  entertainment    1481   \n",
       "7  Fockers retain film chart crown\\n\\nComedy Meet...  entertainment    1821   \n",
       "8  Top gig award for Scissor Sisters\\n\\nNew York ...  entertainment    1238   \n",
       "9  Johnny Depp: The acting outlaw\\n\\nJohnny Depp,...  entertainment    3092   \n",
       "\n",
       "                                        preprocessed  length_after_cleaning  \n",
       "0  musician tackle u red tape musician group tack...                   1461  \n",
       "1  u desire number one u three prestigious grammy...                   3027  \n",
       "2  rocker doherty onstage fight rock singer pete ...                   1420  \n",
       "3  snicket top u box office chart film adaptation...                    746  \n",
       "4  ocean twelve raid box office ocean twelve crim...                   1130  \n",
       "5  landmark movie hailed u film professional decl...                   1538  \n",
       "6  pete doherty miss bail deadline singer pete do...                   1018  \n",
       "7  fockers retain film chart crown comedy meet fo...                   1139  \n",
       "8  top gig award scissor sister new york band sci...                    854  \n",
       "9  johnny depp acting outlaw johnny depp whose la...                   2249  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bbc_data['length_after_cleaning'] = bbc_data['preprocessed'].apply(lambda x: len(x))\n",
    "bbc_data.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ae95a1bf-e26a-4f31-8df1-75967c1234bf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Category of the First Document: entertainment\n",
      "Length of the Text: 1461\n",
      "Full Text of the First Document:\n",
      "musician tackle u red tape musician group tackle u visa regulation blamed hindering british act chance succeeding across atlantic singer hoping perform u expect pay simply obtaining visa group including musician union calling end raw deal faced british performer u act faced comparable expense bureaucracy visiting uk promotional purpose nigel mccune musician union said british musician disadvantaged compared u counterpart sponsor make petition behalf form amounting nearly page musician face tougher regulation athlete journalist make mistake form risk fiveyear ban thus ability career say mr mccune u world biggest music market mean something done creaky bureaucracy say mr mccune current situation preventing british act maintaining momentum developing u added musician union stance endorsed music manager forum mmf say british artist face uphill struggle succeed u thanks tough visa requirement also seen impractical mmfs general secretary james seller said imagine orchestra orkneys every member would travel london visa processed u market seen holy grail one benchmark success still going fight get still important market like europe india china added mr seller department medium culture sport spokeswoman said aware people experiencing problem working u embassy record industry see u embassy spokesman said aware entertainer require visa timespecific visa everything process application speedily aware importance cultural exchange best facilitate added\n"
     ]
    }
   ],
   "source": [
    "print(\"Category of the First Document:\", bbc_data.iloc[0]['category'])  # Print the category of the first document\n",
    "print(\"Length of the Text:\", len(bbc_data.iloc[0]['preprocessed']))  # Print the length of the text in the first document\n",
    "print(\"Full Text of the First Document:\")\n",
    "print(bbc_data.iloc[0]['preprocessed'])  # Print the full text of the first document"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4a35c86-32f2-4811-ab33-fa6d09aa4456",
   "metadata": {},
   "source": [
    "## Train Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d0cc6540-0885-4dfb-90bd-f1d1ae73324e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of X_train: (1557,)\n",
      "Shape of X_test: (668,)\n",
      "Shape of y_train: (1557,)\n",
      "Shape of y_test: (668,)\n"
     ]
    }
   ],
   "source": [
    "# Split data into training and testing sets\n",
    "X_train, X_test, y_train, y_test = train_test_split(bbc_data['preprocessed'], bbc_data['category'], test_size=0.3, random_state=42)\n",
    "\n",
    "print(\"Shape of X_train:\", X_train.shape)\n",
    "print(\"Shape of X_test:\", X_test.shape)\n",
    "print(\"Shape of y_train:\", y_train.shape)\n",
    "print(\"Shape of y_test:\", y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae40a2d7-bb0e-4a7f-9fc2-0dc20f0ca8b3",
   "metadata": {},
   "source": [
    "###  FEATURE EXTRACTION "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b04b019d-3d90-4f4a-83dd-3efb165ef4e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# TF- IDF\n",
    "\n",
    "tfidf_vectorizer = TfidfVectorizer()\n",
    "\n",
    "X_train_tfidf = tfidf_vectorizer.fit_transform(X_train)\n",
    "X_test_tfidf = tfidf_vectorizer.transform(X_test)\n",
    "\n",
    "\n",
    "# Bag of Words\n",
    "count_vectorizer = CountVectorizer()\n",
    "X_train_bow = count_vectorizer.fit_transform(X_train)\n",
    "X_test_bow = count_vectorizer.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37c513cf-8a41-4c2d-9f56-ce78f02c847f",
   "metadata": {},
   "source": [
    "## Machine Learning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab99c2b4-ac82-45e4-860c-9012df5ac78d",
   "metadata": {},
   "source": [
    "## Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bb1effba-29ee-4eab-9f3b-4e83bc888cc3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forest accuracy: 0.9746\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "     business       0.95      0.99      0.97       163\n",
      "entertainment       0.99      0.96      0.97       120\n",
      "     politics       0.97      0.96      0.97       112\n",
      "        sport       1.00      0.99      1.00       148\n",
      "         tech       0.97      0.96      0.96       125\n",
      "\n",
      "     accuracy                           0.97       668\n",
      "    macro avg       0.98      0.97      0.97       668\n",
      " weighted avg       0.97      0.97      0.97       668\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Random Forest + TF-IDF \n",
    "\n",
    "classifier_rf = RandomForestClassifier()\n",
    "\n",
    "\n",
    "classifier_rf.fit(X_train_tfidf, y_train)\n",
    "y_pred_rf = classifier_rf.predict(X_test_tfidf)\n",
    "\n",
    "def evaluate_model(true_labels, predicted_labels, model_name):\n",
    "\n",
    "    accuracy = accuracy_score(true_labels, predicted_labels)\n",
    "    print(f\"{model_name} accuracy: {accuracy:.4f}\")\n",
    "    print(classification_report(true_labels, predicted_labels))\n",
    "    cm = confusion_matrix(true_labels, predicted_labels, labels=np.unique(true_labels))\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=np.unique(true_labels), yticklabels=np.unique(true_labels))\n",
    "    plt.xlabel('Predicted')\n",
    "    plt.ylabel('True')\n",
    "    plt.title(f'Confusion Matrix TF-IDF - {model_name}')\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "evaluate_model(y_test, y_pred_rf, \"Random Forest\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6ac6d1b6-cbf5-44d4-adb1-970e08a9fddf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random Forest accuracy: 0.9656\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "     business       0.92      0.99      0.95       163\n",
      "entertainment       0.98      0.95      0.97       120\n",
      "     politics       0.97      0.97      0.97       112\n",
      "        sport       0.99      0.99      0.99       148\n",
      "         tech       0.98      0.91      0.95       125\n",
      "\n",
      "     accuracy                           0.97       668\n",
      "    macro avg       0.97      0.96      0.97       668\n",
      " weighted avg       0.97      0.97      0.97       668\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Random Forest + Bag of Words\n",
    "\n",
    "classifier_rf = RandomForestClassifier()\n",
    "\n",
    "# Fit the classifier to the training data\n",
    "classifier_rf.fit(X_train_bow, y_train)\n",
    "\n",
    "# Predict labels for the test data\n",
    "y_pred_rf = classifier_rf.predict(X_test_bow)\n",
    "\n",
    "# Evaluation function\n",
    "def evaluate_model(true_labels, predicted_labels, model_name):\n",
    "    accuracy = accuracy_score(true_labels, predicted_labels)\n",
    "    print(f\"{model_name} accuracy: {accuracy:.4f}\")\n",
    "    print(classification_report(true_labels, predicted_labels))\n",
    "    cm = confusion_matrix(true_labels, predicted_labels, labels=np.unique(true_labels))\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=np.unique(true_labels), yticklabels=np.unique(true_labels))\n",
    "    plt.xlabel('Predicted')\n",
    "    plt.ylabel('True')\n",
    "    plt.title(f'Confusion Matrix BOW- {model_name}')\n",
    "    plt.show()\n",
    "\n",
    "# Evaluate the Random Forest classifier\n",
    "evaluate_model(y_test, y_pred_rf, \"Random Forest\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7880285a-3b99-4e3e-86d8-85da984bffc7",
   "metadata": {},
   "source": [
    "## SVM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "85f25608-ccc7-4afe-bf74-7bcfd0d7546e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SVM accuracy: 0.9775\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "     business       0.98      0.98      0.98       163\n",
      "entertainment       0.96      0.97      0.97       120\n",
      "     politics       0.96      0.99      0.97       112\n",
      "        sport       1.00      0.99      1.00       148\n",
      "         tech       0.99      0.95      0.97       125\n",
      "\n",
      "     accuracy                           0.98       668\n",
      "    macro avg       0.98      0.98      0.98       668\n",
      " weighted avg       0.98      0.98      0.98       668\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## SVM + TF-IDF \n",
    "\n",
    "classifier_svm = SVC()\n",
    "\n",
    "\n",
    "classifier_svm.fit(X_train_tfidf, y_train)\n",
    "y_pred_svm = classifier_svm.predict(X_test_tfidf)\n",
    "\n",
    "def evaluate_model(true_labels, predicted_labels, model_name):\n",
    "\n",
    "    accuracy = accuracy_score(true_labels, predicted_labels)\n",
    "    print(f\"{model_name} accuracy: {accuracy:.4f}\")\n",
    "    print(classification_report(true_labels, predicted_labels))\n",
    "    cm = confusion_matrix(true_labels, predicted_labels, labels=np.unique(true_labels))\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=np.unique(true_labels), yticklabels=np.unique(true_labels))\n",
    "    plt.xlabel('Predicted')\n",
    "    plt.ylabel('True')\n",
    "    plt.title(f'Confusion Matrix TF-IDF {model_name}')\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "evaluate_model(y_test, y_pred_svm, \"SVM\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1a85ab82-025f-4e62-82a5-ed90f25dee34",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SVM accuracy: 0.9626\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "     business       0.97      0.96      0.97       163\n",
      "entertainment       0.98      0.92      0.95       120\n",
      "     politics       0.95      0.98      0.96       112\n",
      "        sport       1.00      0.98      0.99       148\n",
      "         tech       0.90      0.98      0.94       125\n",
      "\n",
      "     accuracy                           0.96       668\n",
      "    macro avg       0.96      0.96      0.96       668\n",
      " weighted avg       0.96      0.96      0.96       668\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## SVM + Bag of Words\n",
    "\n",
    "\n",
    "classifier_svm = SVC()\n",
    "\n",
    "\n",
    "classifier_svm.fit(X_train_bow, y_train)\n",
    "y_pred_svm = classifier_svm.predict(X_test_bow)\n",
    "\n",
    "def evaluate_model(true_labels, predicted_labels, model_name):\n",
    "\n",
    "    accuracy = accuracy_score(true_labels, predicted_labels)\n",
    "    print(f\"{model_name} accuracy: {accuracy:.4f}\")\n",
    "    print(classification_report(true_labels, predicted_labels))\n",
    "    cm = confusion_matrix(true_labels, predicted_labels, labels=np.unique(true_labels))\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=np.unique(true_labels), yticklabels=np.unique(true_labels))\n",
    "    plt.xlabel('Predicted')\n",
    "    plt.ylabel('True')\n",
    "    plt.title(f'Confusion Matrix BOW - {model_name}')\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "evaluate_model(y_test, y_pred_svm, \"SVM\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cd94678-45b5-4045-90b0-7f81f1b6d320",
   "metadata": {},
   "source": [
    "## Naive Bayes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8d4419ac-7a30-498c-9d18-af92b270791a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive Bayes accuracy: 0.9671\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "     business       0.96      0.98      0.97       163\n",
      "entertainment       0.99      0.93      0.96       120\n",
      "     politics       0.91      0.98      0.94       112\n",
      "        sport       0.99      0.99      0.99       148\n",
      "         tech       0.99      0.94      0.96       125\n",
      "\n",
      "     accuracy                           0.97       668\n",
      "    macro avg       0.97      0.97      0.97       668\n",
      " weighted avg       0.97      0.97      0.97       668\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Naive Bayes + TF-IDF \n",
    "\n",
    "classifier_nbs = MultinomialNB()\n",
    "\n",
    "\n",
    "classifier_nbs.fit(X_train_tfidf, y_train)\n",
    "y_pred_nbs = classifier_nbs.predict(X_test_tfidf)\n",
    "\n",
    "def evaluate_model(true_labels, predicted_labels, model_name):\n",
    "\n",
    "    accuracy = accuracy_score(true_labels, predicted_labels)\n",
    "    print(f\"{model_name} accuracy: {accuracy:.4f}\")\n",
    "    print(classification_report(true_labels, predicted_labels))\n",
    "    cm = confusion_matrix(true_labels, predicted_labels, labels=np.unique(true_labels))\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=np.unique(true_labels), yticklabels=np.unique(true_labels))\n",
    "    plt.xlabel('Predicted')\n",
    "    plt.ylabel('True')\n",
    "    plt.title(f'Confusion Matrix TF-IDF - {model_name}')\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "evaluate_model(y_test, y_pred_nbs, \"Naive Bayes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1970a071-2851-47db-9ae5-2b690a21b817",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Naive Bayes accuracy: 0.9775\n",
      "               precision    recall  f1-score   support\n",
      "\n",
      "     business       0.98      0.96      0.97       163\n",
      "entertainment       0.99      0.97      0.98       120\n",
      "     politics       0.96      0.98      0.97       112\n",
      "        sport       1.00      0.99      1.00       148\n",
      "         tech       0.96      0.98      0.97       125\n",
      "\n",
      "     accuracy                           0.98       668\n",
      "    macro avg       0.98      0.98      0.98       668\n",
      " weighted avg       0.98      0.98      0.98       668\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## Naive Bayes + Bag of Words\n",
    "\n",
    "classifier_nbs = MultinomialNB()\n",
    "\n",
    "\n",
    "classifier_nbs.fit(X_train_bow, y_train)\n",
    "y_pred_nbs = classifier_nbs.predict(X_test_bow)\n",
    "\n",
    "\n",
    "def evaluate_model(true_labels, predicted_labels, model_name):\n",
    "\n",
    "    accuracy = accuracy_score(true_labels, predicted_labels)\n",
    "    print(f\"{model_name} accuracy: {accuracy:.4f}\")\n",
    "    print(classification_report(true_labels, predicted_labels))\n",
    "    cm = confusion_matrix(true_labels, predicted_labels, labels=np.unique(true_labels))\n",
    "    plt.figure(figsize=(8, 6))\n",
    "    sns.heatmap(cm, annot=True, fmt='d', cmap='Blues', xticklabels=np.unique(true_labels), yticklabels=np.unique(true_labels))\n",
    "    plt.xlabel('Predicted')\n",
    "    plt.ylabel('True')\n",
    "    plt.title(f'Confusion Matrix BOW - {model_name}')\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "evaluate_model(y_test, y_pred_nbs, \"Naive Bayes\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e4e91cd3-6368-4fac-9dda-c0a8070f77f6",
   "metadata": {},
   "source": [
    "## Reference"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad66854b-51da-4d51-a637-b17beb318d85",
   "metadata": {},
   "source": [
    "# The code used in this document is sourced from Python documentation, as well as lecture modules on image processing for data science."
   ]
  }
 ],
 "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
}