movie-genre-classification.ipynb

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   "source": [
    "#### In this machine learning project, we aim to predict the genre of a movie based on its plot summary using various natural language processing (NLP) techniques and machine learning algorithms. We will leverage techniques like TF-IDF (Term Frequency-Inverse Document Frequency) and classifiers such as Naive Bayes, Logistic Regression, or Support Vector Machines (SVM) to build an accurate genre classification model."
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   },
   "source": [
    "# Import nacessary libaries"
   ]
  },
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     "text": [
      "/opt/conda/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.5\n",
      "  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n",
      "/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/__init__.py:98: UserWarning: unable to load libtensorflow_io_plugins.so: unable to open file: libtensorflow_io_plugins.so, from paths: ['/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/libtensorflow_io_plugins.so']\n",
      "caused by: ['/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/libtensorflow_io_plugins.so: undefined symbol: _ZN3tsl6StatusC1EN10tensorflow5error4CodeESt17basic_string_viewIcSt11char_traitsIcEENS_14SourceLocationE']\n",
      "  warnings.warn(f\"unable to load libtensorflow_io_plugins.so: {e}\")\n",
      "/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/__init__.py:104: UserWarning: file system plugins are not loaded: unable to open file: libtensorflow_io.so, from paths: ['/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/libtensorflow_io.so']\n",
      "caused by: ['/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/libtensorflow_io.so: undefined symbol: _ZTVN10tensorflow13GcsFileSystemE']\n",
      "  warnings.warn(f\"file system plugins are not loaded: {e}\")\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import re\n",
    "import string\n",
    "import nltk\n",
    "from nltk.corpus import stopwords\n",
    "from nltk.stem import LancasterStemmer\n",
    "from collections import Counter\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.metrics import classification_report, accuracy_score\n",
    "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Embedding, LSTM, Dense, Dropout, SpatialDropout1D\n",
    "from tensorflow.keras.callbacks import EarlyStopping"
   ]
  },
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   "cell_type": "markdown",
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    "tags": []
   },
   "source": [
    "# Data Preprocessing\n",
    "### Load and preprocess data\n"
   ]
  },
  {
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       "      <th>Title</th>\n",
       "      <th>Genre</th>\n",
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       "      <td>Cupid (1997)</td>\n",
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       "      <td>Young, Wild and Wonderful (1980)</td>\n",
       "      <td>adult</td>\n",
       "      <td>As the bus empties the students for their fie...</td>\n",
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       "                                Title       Genre  \\\n",
       "1       Oscar et la dame rose (2009)       drama    \n",
       "2                       Cupid (1997)    thriller    \n",
       "3   Young, Wild and Wonderful (1980)       adult    \n",
       "4              The Secret Sin (1915)       drama    \n",
       "5             The Unrecovered (2007)       drama    \n",
       "\n",
       "                                         Description  \n",
       "1   Listening in to a conversation between his do...  \n",
       "2   A brother and sister with a past incestuous r...  \n",
       "3   As the bus empties the students for their fie...  \n",
       "4   To help their unemployed father make ends mee...  \n",
       "5   The film's title refers not only to the un-re...  "
      ]
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     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "train_path='/kaggle/input/genre-classification-dataset-imdb/Genre Classification Dataset/train_data.txt'\n",
    "train_data=pd.read_csv( train_path , sep=':::',engine='python',names=['Title','Genre','Description'])\n",
    "train_data.head()"
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Edgar's Lunch (1998)</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>La guerra de papá (1977)</td>\n",
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       "      <th>2</th>\n",
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       "      <td>Off the Beaten Track (2010)</td>\n",
       "      <td>One year in the life of Albin and his family ...</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <th>4</th>\n",
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       "   ID                          Title  \\\n",
       "0   1          Edgar's Lunch (1998)    \n",
       "1   2      La guerra de papá (1977)    \n",
       "2   3   Off the Beaten Track (2010)    \n",
       "3   4        Meu Amigo Hindu (2015)    \n",
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       "                                         Description  \n",
       "0   L.R. Brane loves his life - his car, his apar...  \n",
       "1   Spain, March 1964: Quico is a very naughty ch...  \n",
       "2   One year in the life of Albin and his family ...  \n",
       "3   His father has died, he hasn't spoken with hi...  \n",
       "4   Before he was known internationally as a mart...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "test_path='/kaggle/input/genre-classification-dataset-imdb/Genre Classification Dataset/test_data.txt'\n",
    "test_data=pd.read_csv( test_path , sep=':::',engine='python',names=['ID', 'Title','Description'])\n",
    "test_data.head()"
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       "      <td>Grammy - music award of the American academy ...</td>\n",
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       "                                 Title    Genre  \\\n",
       "count                            54214    54214   \n",
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       "top      Oscar et la dame rose (2009)    drama    \n",
       "freq                                 1    13613   \n",
       "\n",
       "                                              Description  \n",
       "count                                               54214  \n",
       "unique                                              54086  \n",
       "top      Grammy - music award of the American academy ...  \n",
       "freq                                                   12  "
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   "source": [
    "train_data.describe()"
   ]
  },
  {
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    "tags": []
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 54214 entries, 1 to 54214\n",
      "Data columns (total 3 columns):\n",
      " #   Column       Non-Null Count  Dtype \n",
      "---  ------       --------------  ----- \n",
      " 0   Title        54214 non-null  object\n",
      " 1   Genre        54214 non-null  object\n",
      " 2   Description  54214 non-null  object\n",
      "dtypes: object(3)\n",
      "memory usage: 1.7+ MB\n"
     ]
    }
   ],
   "source": [
    "train_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d81d79ac",
   "metadata": {
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    "collapsed": false,
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    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Title          0\n",
       "Genre          0\n",
       "Description    0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "train_data.isnull().sum()"
   ]
  },
  {
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    "tags": []
   },
   "source": [
    "# Data visualizations"
   ]
  },
  {
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     "duration": 0.467176,
     "end_time": "2023-08-17T13:33:54.963250",
     "exception": false,
     "start_time": "2023-08-17T13:33:54.496074",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Count')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "counts = train_data.Genre.value_counts()\n",
    "sns.barplot(x=counts, y=counts.index, orient='h')  \n",
    "plt.xlabel('Genre')\n",
    "plt.ylabel('Count')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "12cd89d6",
   "metadata": {
    "_cell_guid": "bb0b3b8e-317d-46d7-831b-fa76aa7a4257",
    "_uuid": "9f6a60d5-a3c7-4695-908a-52106709dd03",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:33:54.984321Z",
     "iopub.status.busy": "2023-08-17T13:33:54.983255Z",
     "iopub.status.idle": "2023-08-17T13:33:55.471027Z",
     "shell.execute_reply": "2023-08-17T13:33:55.469951Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 0.500747,
     "end_time": "2023-08-17T13:33:55.473061",
     "exception": false,
     "start_time": "2023-08-17T13:33:54.972314",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,8))\n",
    "counts = train_data.Genre.value_counts()\n",
    "sns.barplot(x=counts.index, y=counts, color='blue')\n",
    "plt.xlabel('Genre' ,fontsize=14, fontweight='bold')\n",
    "plt.ylabel('Count', fontsize=14, fontweight='bold')\n",
    "plt.title('Distribution of Genres', fontsize=16, fontweight='bold')\n",
    "plt.xticks(rotation=90, fontsize=14, fontweight='bold');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b67ab3e4",
   "metadata": {
    "_cell_guid": "335ce5e5-a910-4980-84f7-db354e422403",
    "_uuid": "0e82b19d-4d1a-44ff-993c-b556e1c150f3",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:33:55.494530Z",
     "iopub.status.busy": "2023-08-17T13:33:55.493445Z",
     "iopub.status.idle": "2023-08-17T13:33:55.524106Z",
     "shell.execute_reply": "2023-08-17T13:33:55.522967Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 0.04391,
     "end_time": "2023-08-17T13:33:55.526532",
     "exception": false,
     "start_time": "2023-08-17T13:33:55.482622",
     "status": "completed"
    },
    "tags": []
   },
   "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>Title</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Description</th>\n",
       "      <th>length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Oscar et la dame rose (2009)</td>\n",
       "      <td>drama</td>\n",
       "      <td>Listening in to a conversation between his do...</td>\n",
       "      <td>546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cupid (1997)</td>\n",
       "      <td>thriller</td>\n",
       "      <td>A brother and sister with a past incestuous r...</td>\n",
       "      <td>184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Young, Wild and Wonderful (1980)</td>\n",
       "      <td>adult</td>\n",
       "      <td>As the bus empties the students for their fie...</td>\n",
       "      <td>650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Secret Sin (1915)</td>\n",
       "      <td>drama</td>\n",
       "      <td>To help their unemployed father make ends mee...</td>\n",
       "      <td>1082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>The Unrecovered (2007)</td>\n",
       "      <td>drama</td>\n",
       "      <td>The film's title refers not only to the un-re...</td>\n",
       "      <td>625</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Title       Genre  \\\n",
       "1       Oscar et la dame rose (2009)       drama    \n",
       "2                       Cupid (1997)    thriller    \n",
       "3   Young, Wild and Wonderful (1980)       adult    \n",
       "4              The Secret Sin (1915)       drama    \n",
       "5             The Unrecovered (2007)       drama    \n",
       "\n",
       "                                         Description  length  \n",
       "1   Listening in to a conversation between his do...     546  \n",
       "2   A brother and sister with a past incestuous r...     184  \n",
       "3   As the bus empties the students for their fie...     650  \n",
       "4   To help their unemployed father make ends mee...    1082  \n",
       "5   The film's title refers not only to the un-re...     625  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data['length']=train_data['Description'].apply(len)\n",
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "3cb846e1",
   "metadata": {
    "_cell_guid": "d0df3558-89da-43b9-bcc0-0a11ab260d02",
    "_uuid": "80f112ef-d22f-4ada-84c3-29c65fb9f4c0",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:33:55.549112Z",
     "iopub.status.busy": "2023-08-17T13:33:55.548319Z",
     "iopub.status.idle": "2023-08-17T13:33:56.089397Z",
     "shell.execute_reply": "2023-08-17T13:33:56.087745Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 0.55514,
     "end_time": "2023-08-17T13:33:56.092023",
     "exception": false,
     "start_time": "2023-08-17T13:33:55.536883",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 7))\n",
    "\n",
    "sns.histplot(data=train_data, x='length', bins=20, kde=True, color='blue')\n",
    "\n",
    "plt.xlabel('Length', fontsize=14, fontweight='bold')\n",
    "plt.ylabel('Frequency', fontsize=14, fontweight='bold')\n",
    "plt.title('Distribution of Lengths', fontsize=16, fontweight='bold')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16fcf8fc",
   "metadata": {
    "_cell_guid": "02f4411e-0637-49b7-adec-2f9994d9d6bb",
    "_uuid": "a750b876-31d6-42fc-b931-e123ff89323a",
    "papermill": {
     "duration": 0.009499,
     "end_time": "2023-08-17T13:33:56.111639",
     "exception": false,
     "start_time": "2023-08-17T13:33:56.102140",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Data cleaning and preprocessing\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "65021ea3",
   "metadata": {
    "_cell_guid": "b9c5c344-1b45-468c-952a-16896d7a863f",
    "_uuid": "341460dd-9575-48a6-ad0c-78b96d592dd8",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:33:56.134292Z",
     "iopub.status.busy": "2023-08-17T13:33:56.132799Z",
     "iopub.status.idle": "2023-08-17T13:33:56.158157Z",
     "shell.execute_reply": "2023-08-17T13:33:56.157115Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 0.038527,
     "end_time": "2023-08-17T13:33:56.160118",
     "exception": false,
     "start_time": "2023-08-17T13:33:56.121591",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original text: Certainly you get a dramatic boost from hello bye the the hi -iv iem-k q934*2yee !*3 2e38\n",
      "Cleaned text: certain get dram boost hello bye iem\n"
     ]
    }
   ],
   "source": [
    "stemmer = LancasterStemmer()\n",
    "stop_words = set(stopwords.words('english'))\n",
    "\n",
    "def clean_text(text):\n",
    "   \n",
    "    text = text.lower()                                  # lower-case all characters\n",
    "    text = re.sub('-',' ',text.lower())   # replace `word-word` as `word word`\n",
    "    text = re.sub(f'[{string.digits}]',' ',text)  # remove digits\n",
    "    text = ' '.join([stemmer.stem(word) for word in text.split() if word not in stop_words])  # remove stopwords and stem other words\n",
    "    text =  re.sub(r'@\\S+', '',text)                     # remove twitter handles\n",
    "    text =  re.sub(r'http\\S+', '',text)                  # remove urls\n",
    "    text =  re.sub(r'pic.\\S+', '',text) \n",
    "    text =  re.sub(r\"[^a-zA-Z+']\", ' ',text)             # only keeps characters\n",
    "    text = re.sub(r'\\s+[a-zA-Z]\\s+', ' ', text+' ')      # keep words with length>1 only\n",
    "    text = \"\".join([i for i in text if i not in string.punctuation])\n",
    "    words = nltk.tokenize.word_tokenize(text,language=\"english\", preserve_line=True)\n",
    "    stopwords = nltk.corpus.stopwords.words('english')   # remove stopwords\n",
    "    text = \" \".join([i for i in words if i not in stopwords and len(i)>2])\n",
    "    text= re.sub(\"\\s[\\s]+\", \" \",text).strip()            # remove repeated/leading/trailing spaces\n",
    "    return re.sub(f'[{re.escape(string.punctuation)}]','',text) # remove punctuations\n",
    "\n",
    "\n",
    "# Test your cleaning function\n",
    "input_text = \"Certainly you get a dramatic boost from hello bye the the hi -iv iem-k q934*2yee !*3 2e38\"\n",
    "print(f'Original text: {input_text}')\n",
    "print(f'Cleaned text: {clean_text(input_text)}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "60547be9",
   "metadata": {
    "_cell_guid": "d9a884b3-8955-435c-b2e8-a00b67a6723c",
    "_uuid": "146c0195-7fed-40b4-92f2-60f9980490bd",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:33:56.181556Z",
     "iopub.status.busy": "2023-08-17T13:33:56.181242Z",
     "iopub.status.idle": "2023-08-17T13:36:30.078110Z",
     "shell.execute_reply": "2023-08-17T13:36:30.076611Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 153.918953,
     "end_time": "2023-08-17T13:36:30.089266",
     "exception": false,
     "start_time": "2023-08-17T13:33:56.170313",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Description</th>\n",
       "      <th>length</th>\n",
       "      <th>Text_cleaning</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Oscar et la dame rose (2009)</td>\n",
       "      <td>drama</td>\n",
       "      <td>Listening in to a conversation between his do...</td>\n",
       "      <td>546</td>\n",
       "      <td>list convers doct parents year old osc learn n...</td>\n",
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       "      <th>2</th>\n",
       "      <td>Cupid (1997)</td>\n",
       "      <td>thriller</td>\n",
       "      <td>A brother and sister with a past incestuous r...</td>\n",
       "      <td>184</td>\n",
       "      <td>broth sist past incestu rel cur murd relations...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Young, Wild and Wonderful (1980)</td>\n",
       "      <td>adult</td>\n",
       "      <td>As the bus empties the students for their fie...</td>\n",
       "      <td>650</td>\n",
       "      <td>bus empty stud field trip muse nat history lit...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Secret Sin (1915)</td>\n",
       "      <td>drama</td>\n",
       "      <td>To help their unemployed father make ends mee...</td>\n",
       "      <td>1082</td>\n",
       "      <td>help unemploy fath mak end meet edi twin sist ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>The Unrecovered (2007)</td>\n",
       "      <td>drama</td>\n",
       "      <td>The film's title refers not only to the un-re...</td>\n",
       "      <td>625</td>\n",
       "      <td>films titl ref recov body ground zero also sta...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Title       Genre  \\\n",
       "1       Oscar et la dame rose (2009)       drama    \n",
       "2                       Cupid (1997)    thriller    \n",
       "3   Young, Wild and Wonderful (1980)       adult    \n",
       "4              The Secret Sin (1915)       drama    \n",
       "5             The Unrecovered (2007)       drama    \n",
       "\n",
       "                                         Description  length  \\\n",
       "1   Listening in to a conversation between his do...     546   \n",
       "2   A brother and sister with a past incestuous r...     184   \n",
       "3   As the bus empties the students for their fie...     650   \n",
       "4   To help their unemployed father make ends mee...    1082   \n",
       "5   The film's title refers not only to the un-re...     625   \n",
       "\n",
       "                                       Text_cleaning  \n",
       "1  list convers doct parents year old osc learn n...  \n",
       "2  broth sist past incestu rel cur murd relations...  \n",
       "3  bus empty stud field trip muse nat history lit...  \n",
       "4  help unemploy fath mak end meet edi twin sist ...  \n",
       "5  films titl ref recov body ground zero also sta...  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data['Text_cleaning'] = train_data.Description.apply(clean_text)\n",
    "test_data['Text_cleaning'] = test_data.Description.apply(clean_text)\n",
    "\n",
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0d14c149",
   "metadata": {
    "_cell_guid": "9109c780-a145-4c41-9c42-71e4b59e44c4",
    "_uuid": "9bb73cde-0c41-430a-9191-6f7dd0426132",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:36:30.111677Z",
     "iopub.status.busy": "2023-08-17T13:36:30.111280Z",
     "iopub.status.idle": "2023-08-17T13:36:30.144622Z",
     "shell.execute_reply": "2023-08-17T13:36:30.143374Z"
    },
    "jupyter": {
     "outputs_hidden": false
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    "papermill": {
     "duration": 0.047421,
     "end_time": "2023-08-17T13:36:30.146966",
     "exception": false,
     "start_time": "2023-08-17T13:36:30.099545",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Title</th>\n",
       "      <th>Genre</th>\n",
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       "      <th>length</th>\n",
       "      <th>Text_cleaning</th>\n",
       "      <th>length_Text_cleaning</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Oscar et la dame rose (2009)</td>\n",
       "      <td>drama</td>\n",
       "      <td>Listening in to a conversation between his do...</td>\n",
       "      <td>546</td>\n",
       "      <td>list convers doct parents year old osc learn n...</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Cupid (1997)</td>\n",
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       "      <td>A brother and sister with a past incestuous r...</td>\n",
       "      <td>184</td>\n",
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       "      <td>Young, Wild and Wonderful (1980)</td>\n",
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       "      <td>As the bus empties the students for their fie...</td>\n",
       "      <td>650</td>\n",
       "      <td>bus empty stud field trip muse nat history lit...</td>\n",
       "      <td>325</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>The Secret Sin (1915)</td>\n",
       "      <td>drama</td>\n",
       "      <td>To help their unemployed father make ends mee...</td>\n",
       "      <td>1082</td>\n",
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       "      <td>616</td>\n",
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       "      <th>5</th>\n",
       "      <td>The Unrecovered (2007)</td>\n",
       "      <td>drama</td>\n",
       "      <td>The film's title refers not only to the un-re...</td>\n",
       "      <td>625</td>\n",
       "      <td>films titl ref recov body ground zero also sta...</td>\n",
       "      <td>282</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Title       Genre  \\\n",
       "1       Oscar et la dame rose (2009)       drama    \n",
       "2                       Cupid (1997)    thriller    \n",
       "3   Young, Wild and Wonderful (1980)       adult    \n",
       "4              The Secret Sin (1915)       drama    \n",
       "5             The Unrecovered (2007)       drama    \n",
       "\n",
       "                                         Description  length  \\\n",
       "1   Listening in to a conversation between his do...     546   \n",
       "2   A brother and sister with a past incestuous r...     184   \n",
       "3   As the bus empties the students for their fie...     650   \n",
       "4   To help their unemployed father make ends mee...    1082   \n",
       "5   The film's title refers not only to the un-re...     625   \n",
       "\n",
       "                                       Text_cleaning  length_Text_cleaning  \n",
       "1  list convers doct parents year old osc learn n...                   324  \n",
       "2  broth sist past incestu rel cur murd relations...                    83  \n",
       "3  bus empty stud field trip muse nat history lit...                   325  \n",
       "4  help unemploy fath mak end meet edi twin sist ...                   616  \n",
       "5  films titl ref recov body ground zero also sta...                   282  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data['length_Text_cleaning']=train_data['Text_cleaning'].apply(len)\n",
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bdfb7076",
   "metadata": {
    "_cell_guid": "5c7e3e0e-3a68-4b9c-bc03-1d46f559129b",
    "_uuid": "9221b725-b733-48a0-ae47-eb3fed190eca",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:36:30.169563Z",
     "iopub.status.busy": "2023-08-17T13:36:30.169157Z",
     "iopub.status.idle": "2023-08-17T13:36:30.835580Z",
     "shell.execute_reply": "2023-08-17T13:36:30.833480Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
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     "exception": false,
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     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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AUO3QKwG1D1/ZA4AqMHnyZPXo0UOBgYH66KOPtGDBAs2cObOqhwUAAFAt0CsBtR8rpACgCgwcOFCfffaZDh8+rBYtWmjUqFG6//77q3pYAAAA1QK9ElD7EUgBAAAAAADAVnWqegAAAAAAAAC4tBBIAQAAAAAAwFYEUgAAAAAAALAVgRQAAP+vHTsWAAAAABjkbz2LXYURAACwElIAAAAArIQUAAAAACshBQAAAMBKSAEAAACwElIAAAAArALqhUPD/RyEXgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1200x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create histograms for text length before and after cleaning\n",
    "plt.figure(figsize=(12, 6))\n",
    "\n",
    "# Original text length distribution\n",
    "plt.subplot(1, 2, 1)\n",
    "original_lengths = train_data['Description'].apply(len)\n",
    "plt.hist(original_lengths, bins=range(0, max(original_lengths) + 100, 100), color='blue', alpha=0.7)\n",
    "plt.title('Original Text Length')\n",
    "plt.xlabel('Text Length')\n",
    "plt.ylabel('Frequency')\n",
    "\n",
    "# Cleaned text length distribution\n",
    "plt.subplot(1, 2, 2)\n",
    "cleaned_lengths = train_data['Text_cleaning'].apply(len)\n",
    "plt.hist(cleaned_lengths, bins=range(0, max(cleaned_lengths) + 100, 100), color='green', alpha=0.7)\n",
    "plt.title('Cleaned Text Length')\n",
    "plt.xlabel('Text Length')\n",
    "plt.ylabel('Frequency')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4956fc1a",
   "metadata": {
    "_cell_guid": "7886ee5a-cc95-4f64-aa15-0a3b4394497d",
    "_uuid": "977a8944-35a7-43c2-b341-fe26075a7f32",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:36:30.869611Z",
     "iopub.status.busy": "2023-08-17T13:36:30.869142Z",
     "iopub.status.idle": "2023-08-17T13:36:30.882414Z",
     "shell.execute_reply": "2023-08-17T13:36:30.881460Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 0.029482,
     "end_time": "2023-08-17T13:36:30.884420",
     "exception": false,
     "start_time": "2023-08-17T13:36:30.854938",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    54131\n",
       "True        83\n",
       "Name: length_Text_cleaning, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(train_data['length_Text_cleaning']>2000).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "55de207c",
   "metadata": {
    "_cell_guid": "18e33cbe-4618-4001-8ec7-5ad8ca75463f",
    "_uuid": "d29a8d6e-d09a-403c-8115-2a826e36e90c",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:36:30.908339Z",
     "iopub.status.busy": "2023-08-17T13:36:30.908012Z",
     "iopub.status.idle": "2023-08-17T13:36:30.931043Z",
     "shell.execute_reply": "2023-08-17T13:36:30.929294Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 0.038273,
     "end_time": "2023-08-17T13:36:30.933757",
     "exception": false,
     "start_time": "2023-08-17T13:36:30.895484",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dataframe size (before removal):  54214\n",
      "Dataframe size (after removal):  54131\n",
      "Removed rows: 83\n"
     ]
    }
   ],
   "source": [
    "#Remove extremely long descriptions: outliers\n",
    "print('Dataframe size (before removal): ',len(train_data))\n",
    "filt=train_data['length_Text_cleaning']>2000\n",
    "train_data.drop(train_data[filt].index,axis=0,inplace=True)     # filter rows having cleaned description length > 2000\n",
    "print('Dataframe size (after removal): ',len(train_data))\n",
    "print(f'Removed rows: {filt.sum()}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "dc588a38",
   "metadata": {
    "_cell_guid": "a143597c-5e08-434c-a906-00ea4030aa2f",
    "_uuid": "9b9232bb-760e-4fe6-b841-18ed41ca8121",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:36:30.957931Z",
     "iopub.status.busy": "2023-08-17T13:36:30.957554Z",
     "iopub.status.idle": "2023-08-17T13:36:32.607587Z",
     "shell.execute_reply": "2023-08-17T13:36:32.606766Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 1.664679,
     "end_time": "2023-08-17T13:36:32.609580",
     "exception": false,
     "start_time": "2023-08-17T13:36:30.944901",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,5))\n",
    "sns.barplot(x='Genre',y='length_Text_cleaning',data=train_data)  # from 600ish to 350ish -> significant reduction in length\n",
    "plt.xticks(rotation=60)\n",
    "plt.show()\n",
    "plt.figure(figsize=(20,5))\n",
    "sns.boxplot(x=train_data['length_Text_cleaning'].values,hue='Genre',data=train_data)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef25c29d",
   "metadata": {
    "_cell_guid": "81d8a08b-b00e-4a5f-8f94-76e24fe96007",
    "_uuid": "79da2ea2-3d47-4045-8835-a398c119793e",
    "papermill": {
     "duration": 0.011777,
     "end_time": "2023-08-17T13:36:32.633290",
     "exception": false,
     "start_time": "2023-08-17T13:36:32.621513",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Text tokenization and vectorization\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "4b1d847f",
   "metadata": {
    "_cell_guid": "995f4a5d-16f7-496d-a3e0-04bb921a78f1",
    "_uuid": "07bafe23-9b9b-4ef6-a233-96387061da88",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:36:32.658962Z",
     "iopub.status.busy": "2023-08-17T13:36:32.658012Z",
     "iopub.status.idle": "2023-08-17T13:36:35.743176Z",
     "shell.execute_reply": "2023-08-17T13:36:35.741935Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 3.100475,
     "end_time": "2023-08-17T13:36:35.745549",
     "exception": false,
     "start_time": "2023-08-17T13:36:32.645074",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "num_words = 50000\n",
    "max_len = 250\n",
    "tokenizer = Tokenizer(num_words=num_words, filters='!\"#$%&()*+,-./:;<=>?@[\\]^_`{|}~', lower=True)\n",
    "tokenizer.fit_on_texts(train_data['Text_cleaning'].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "e2cb8710",
   "metadata": {
    "_cell_guid": "42510c52-1d17-4345-ac14-e38090455607",
    "_uuid": "f1d55c9c-00ad-401d-b567-241780420573",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:36:35.772151Z",
     "iopub.status.busy": "2023-08-17T13:36:35.771662Z",
     "iopub.status.idle": "2023-08-17T13:36:36.523934Z",
     "shell.execute_reply": "2023-08-17T13:36:36.523220Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
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     "exception": false,
     "start_time": "2023-08-17T13:36:35.757981",
     "status": "completed"
    },
    "tags": []
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   "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>ID</th>\n",
       "      <th>Title</th>\n",
       "      <th>Genre</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Edgar's Lunch (1998)</td>\n",
       "      <td>thriller</td>\n",
       "      <td>L.R. Brane loves his life - his car, his apar...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>La guerra de papá (1977)</td>\n",
       "      <td>comedy</td>\n",
       "      <td>Spain, March 1964: Quico is a very naughty ch...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Off the Beaten Track (2010)</td>\n",
       "      <td>documentary</td>\n",
       "      <td>One year in the life of Albin and his family ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Meu Amigo Hindu (2015)</td>\n",
       "      <td>drama</td>\n",
       "      <td>His father has died, he hasn't spoken with hi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Er nu zhai (1955)</td>\n",
       "      <td>drama</td>\n",
       "      <td>Before he was known internationally as a mart...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID                          Title          Genre  \\\n",
       "0   1          Edgar's Lunch (1998)       thriller    \n",
       "1   2      La guerra de papá (1977)         comedy    \n",
       "2   3   Off the Beaten Track (2010)    documentary    \n",
       "3   4        Meu Amigo Hindu (2015)          drama    \n",
       "4   5             Er nu zhai (1955)          drama    \n",
       "\n",
       "                                         Description  \n",
       "0   L.R. Brane loves his life - his car, his apar...  \n",
       "1   Spain, March 1964: Quico is a very naughty ch...  \n",
       "2   One year in the life of Albin and his family ...  \n",
       "3   His father has died, he hasn't spoken with hi...  \n",
       "4   Before he was known internationally as a mart...  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_path='/kaggle/input/genre-classification-dataset-imdb/Genre Classification Dataset/test_data_solution.txt'\n",
    "test_data_solution=pd.read_csv( test_path , sep=':::',engine='python',names=['ID','Title','Genre','Description'])\n",
    "test_data_solution.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0031817",
   "metadata": {
    "_cell_guid": "7a10c0e8-d7c1-4e2b-8318-6284e588d8b1",
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     "start_time": "2023-08-17T13:36:36.537869",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#  Text Vectorization (TF-IDF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "6c69c12a",
   "metadata": {
    "_cell_guid": "d81839ae-110e-4b34-87e1-60529972dcc3",
    "_uuid": "0a7e2063-dd4a-4922-8104-d62c83e9f02d",
    "collapsed": false,
    "execution": {
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    },
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     "end_time": "2023-08-17T13:36:41.218816",
     "exception": false,
     "start_time": "2023-08-17T13:36:36.561496",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "X = tokenizer.texts_to_sequences(train_data['Text_cleaning'].values)\n",
    "X = pad_sequences(X, maxlen=max_len)\n",
    "y = pd.get_dummies(train_data['Genre']).values\n",
    "\n",
    "X_test = tokenizer.texts_to_sequences(test_data['Text_cleaning'].values)\n",
    "X_test = pad_sequences(X_test, maxlen=max_len)\n",
    "y_test = pd.get_dummies(test_data_solution['Genre']).values"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d7c3e834",
   "metadata": {
    "_cell_guid": "2496ee22-9703-4428-a6d0-7bf34432356f",
    "_uuid": "6970b567-3ffc-47ee-b2ca-240977923ada",
    "papermill": {
     "duration": 0.011337,
     "end_time": "2023-08-17T13:36:41.242423",
     "exception": false,
     "start_time": "2023-08-17T13:36:41.231086",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Build the LSTM model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "855da841",
   "metadata": {
    "_cell_guid": "045135e4-22a4-43c9-bd95-43844a2e8faf",
    "_uuid": "4bd68a4d-538a-4521-8318-8225319c24e3",
    "collapsed": false,
    "execution": {
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    },
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     "start_time": "2023-08-17T13:36:41.253882",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "EMBEDDING_DIM = 100\n",
    "model = Sequential()\n",
    "model.add(Embedding(num_words, EMBEDDING_DIM, input_length=X.shape[1]))\n",
    "model.add(SpatialDropout1D(0.2))\n",
    "model.add(LSTM(100, dropout=0.1, recurrent_dropout=0.2))\n",
    "model.add(Dense(27, activation='softmax'))\n",
    "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3022f40d",
   "metadata": {
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     "duration": 0.011772,
     "end_time": "2023-08-17T13:36:41.725437",
     "exception": false,
     "start_time": "2023-08-17T13:36:41.713665",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Train the model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3e07a4a4",
   "metadata": {
    "_cell_guid": "fd129c36-666e-4f25-82a6-633cdce56b37",
    "_uuid": "49be5b66-11d9-42c0-b34a-9e6fb701d396",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T13:36:41.752954Z",
     "iopub.status.busy": "2023-08-17T13:36:41.752405Z",
     "iopub.status.idle": "2023-08-17T14:11:51.478374Z",
     "shell.execute_reply": "2023-08-17T14:11:51.476604Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 2110.138633,
     "end_time": "2023-08-17T14:11:51.877062",
     "exception": false,
     "start_time": "2023-08-17T13:36:41.738429",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/6\n",
      "1692/1692 [==============================] - 532s 313ms/step - loss: 1.9974 - accuracy: 0.4199 - val_loss: 1.6832 - val_accuracy: 0.5142\n",
      "Epoch 2/6\n",
      "1692/1692 [==============================] - 529s 313ms/step - loss: 1.4605 - accuracy: 0.5768 - val_loss: 1.5448 - val_accuracy: 0.5489\n",
      "Epoch 3/6\n",
      "1692/1692 [==============================] - 519s 307ms/step - loss: 1.1305 - accuracy: 0.6727 - val_loss: 1.5738 - val_accuracy: 0.5472\n",
      "Epoch 4/6\n",
      "1692/1692 [==============================] - 529s 313ms/step - loss: 0.8539 - accuracy: 0.7519 - val_loss: 1.6869 - val_accuracy: 0.5372\n"
     ]
    }
   ],
   "source": [
    "my_callbacks  = [EarlyStopping(monitor='val_loss',\n",
    "                              min_delta=0,\n",
    "                              patience=2,\n",
    "                              mode='auto')]\n",
    "history = model.fit(X, y, epochs=6, batch_size=32,validation_data=(X_test,y_test), callbacks=my_callbacks)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a0773a5",
   "metadata": {
    "_cell_guid": "212e905d-afdb-4cd3-ae08-caf86c92e973",
    "_uuid": "c59736ac-4869-4ea4-9178-cb07f0726cba",
    "papermill": {
     "duration": 0.39549,
     "end_time": "2023-08-17T14:11:52.664894",
     "exception": false,
     "start_time": "2023-08-17T14:11:52.269404",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Plotting Accuracy & Loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "17602c58",
   "metadata": {
    "_cell_guid": "d64b823a-2aa1-456b-9d8c-5e8ef46c9510",
    "_uuid": "0978bf05-d41a-410b-bd04-1f9248db6277",
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2023-08-17T14:11:53.526832Z",
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     "shell.execute_reply": "2023-08-17T14:11:54.003832Z"
    },
    "jupyter": {
     "outputs_hidden": false
    },
    "papermill": {
     "duration": 0.878081,
     "end_time": "2023-08-17T14:11:54.007297",
     "exception": false,
     "start_time": "2023-08-17T14:11:53.129216",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 4))\n",
    "plt.subplot(1, 2, 1)\n",
    "plt.plot(history.history['accuracy'], label='Train Accuracy')\n",
    "plt.plot(history.history['val_accuracy'], label='Validation Accuracy')\n",
    "plt.legend()\n",
    "plt.title('Accuracy')\n",
    "\n",
    "plt.subplot(1, 2, 2)\n",
    "plt.plot(history.history['loss'], label='Train Loss')\n",
    "plt.plot(history.history['val_loss'], label='Validation Loss')\n",
    "plt.legend()\n",
    "plt.title('Loss')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
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