system2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# System 2:\n",
    "### generating byte frequency distributions derived from file first blocks to train and evaluate our models - FFNN, CNN, GRU, LSTM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from toolkit.utils import get_file_types, get_1st_block_bytes, convert_cat2num, byte_frequency_histogram\n",
    "from toolkit.models import Ffnn, Ffnn2, Cnn, Cnn2, Lstm, Gru\n",
    "from toolkit.metrics import evaluate_performance, plot_confusion_matrix\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import confusion_matrix, classification_report"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Data Preparation\n",
    "we follow the same steps in preparing are data. However, we'll be generating byte frequency distributions to use as feature inputs at the models training stage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dir_path = 'govdocs1/'\n",
    "files_data = get_file_types(dir_path)\n",
    "df = pd.DataFrame(files_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "CLASS_NAMES = [\n",
    "    \"doc\",\n",
    "    \"pdf\",\n",
    "    \"ps\",\n",
    "    \"xls\",\n",
    "    \"ppt\",\n",
    "    \"swf\",\n",
    "    \"gif\",\n",
    "    \"jpg\",\n",
    "    \"png\",\n",
    "    \"html\",\n",
    "    \"txt\",\n",
    "    \"xml\"\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[df['type'].isin(CLASS_NAMES)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The average file size is: 522.8481363551462\n"
     ]
    }
   ],
   "source": [
    "df['size KB'] = df['file'].apply(\n",
    "    lambda x: float(os.path.getsize(\n",
    "        os.path.join(os.getcwd(), f\"govdocs1/{x}\")\n",
    "    ) / 1024) if os.path.isfile(\n",
    "        os.path.join(os.getcwd(), f\"govdocs1/{x}\")\n",
    "    ) else None\n",
    ")\n",
    "\n",
    "print(f\"The average file size is: {df['size KB'].mean()}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_22152\\680528139.py:1: DeprecationWarning: DataFrameGroupBy.apply operated on the grouping columns. This behavior is deprecated, and in a future version of pandas the grouping columns will be excluded from the operation. Either pass `include_groups=False` to exclude the groupings or explicitly select the grouping columns after groupby to silence this warning.\n",
      "  df = df.groupby('type').apply(lambda x: x.sample(n=2000, random_state=42)).reset_index(drop=True)\n"
     ]
    }
   ],
   "source": [
    "df = df.groupby('type').apply(lambda x: x.sample(n=2000, random_state=42)).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_dir = os.path.join(os.getcwd(), \"govdocs1\")\n",
    "df[\"1st_block_bytes\"] = df[\"file\"].apply(lambda file: get_1st_block_bytes(os.path.join(base_dir, file)))\n",
    "df[\"byte_bfh\"] = df[\"1st_block_bytes\"].apply(lambda byte_sequences: byte_frequency_histogram(np.array([byte for byte in byte_sequences])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "byte lengths of each sequence:\n",
      " 0        256\n",
      "1        256\n",
      "2        256\n",
      "3        256\n",
      "4        256\n",
      "        ... \n",
      "23995    256\n",
      "23996    256\n",
      "23997    256\n",
      "23998    256\n",
      "23999    256\n",
      "Name: byte_bfh, Length: 24000, dtype: int64\n",
      "all byte sequences of the same length: True\n"
     ]
    }
   ],
   "source": [
    "# checking that our arrays are homogeneous\n",
    "byte_lengths = df[\"byte_bfh\"].apply(len)\n",
    "all_same_length = byte_lengths.nunique() == 1\n",
    "\n",
    "print(\"byte lengths of each sequence:\\n\", byte_lengths)\n",
    "print(\"all byte sequences of the same length:\", all_same_length)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"class\"] = df[\"type\"].apply(lambda file_type: convert_cat2num(file_type))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>file</th>\n",
       "      <th>type</th>\n",
       "      <th>size KB</th>\n",
       "      <th>1st_block_bytes</th>\n",
       "      <th>byte_bfh</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>780</th>\n",
       "      <td>501464.doc</td>\n",
       "      <td>doc</td>\n",
       "      <td>129.500000</td>\n",
       "      <td>b'\\xd0\\xcf\\x11\\xe0\\xa1\\xb1\\x1a\\xe1\\x00\\x00\\x00...</td>\n",
       "      <td>[1772, 9, 6, 3, 4, 0, 16, 21, 2, 4, 0, 0, 2, 6...</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16100</th>\n",
       "      <td>497142.swf</td>\n",
       "      <td>swf</td>\n",
       "      <td>27.837891</td>\n",
       "      <td>b'FWS\\x04Zo\\x00\\x00x\\x00\\x05\\xfa\\x00\\x00\\x1ex\\...</td>\n",
       "      <td>[302, 81, 54, 31, 62, 39, 61, 29, 32, 44, 25, ...</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13180</th>\n",
       "      <td>377879.ppt</td>\n",
       "      <td>ppt</td>\n",
       "      <td>47751.000000</td>\n",
       "      <td>b'\\xd0\\xcf\\x11\\xe0\\xa1\\xb1\\x1a\\xe1\\x00\\x00\\x00...</td>\n",
       "      <td>[1995, 270, 13, 5, 5, 8, 7, 5, 10, 9, 20, 6, 6...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11924</th>\n",
       "      <td>739517.png</td>\n",
       "      <td>png</td>\n",
       "      <td>62.077148</td>\n",
       "      <td>b'\\x89PNG\\r\\n\\x1a\\n\\x00\\x00\\x00\\rIHDR\\x00\\x00\\...</td>\n",
       "      <td>[210, 15, 21, 17, 11, 27, 15, 9, 16, 7, 22, 14...</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7261</th>\n",
       "      <td>039042.jpg</td>\n",
       "      <td>jpg</td>\n",
       "      <td>49.884766</td>\n",
       "      <td>b'\\xff\\xd8\\xff\\xe0\\x00\\x10JFIF\\x00\\x01\\x02\\x01...</td>\n",
       "      <td>[382, 71, 24, 30, 30, 21, 22, 21, 17, 14, 11, ...</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             file type       size KB  \\\n",
       "780    501464.doc  doc    129.500000   \n",
       "16100  497142.swf  swf     27.837891   \n",
       "13180  377879.ppt  ppt  47751.000000   \n",
       "11924  739517.png  png     62.077148   \n",
       "7261   039042.jpg  jpg     49.884766   \n",
       "\n",
       "                                         1st_block_bytes  \\\n",
       "780    b'\\xd0\\xcf\\x11\\xe0\\xa1\\xb1\\x1a\\xe1\\x00\\x00\\x00...   \n",
       "16100  b'FWS\\x04Zo\\x00\\x00x\\x00\\x05\\xfa\\x00\\x00\\x1ex\\...   \n",
       "13180  b'\\xd0\\xcf\\x11\\xe0\\xa1\\xb1\\x1a\\xe1\\x00\\x00\\x00...   \n",
       "11924  b'\\x89PNG\\r\\n\\x1a\\n\\x00\\x00\\x00\\rIHDR\\x00\\x00\\...   \n",
       "7261   b'\\xff\\xd8\\xff\\xe0\\x00\\x10JFIF\\x00\\x01\\x02\\x01...   \n",
       "\n",
       "                                                byte_bfh  class  \n",
       "780    [1772, 9, 6, 3, 4, 0, 16, 21, 2, 4, 0, 0, 2, 6...      1  \n",
       "16100  [302, 81, 54, 31, 62, 39, 61, 29, 32, 44, 25, ...      6  \n",
       "13180  [1995, 270, 13, 5, 5, 8, 7, 5, 10, 9, 20, 6, 6...      5  \n",
       "11924  [210, 15, 21, 17, 11, 27, 15, 9, 16, 7, 22, 14...      9  \n",
       "7261   [382, 71, 24, 30, 30, 21, 22, 21, 17, 14, 11, ...      8  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(n=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X shape:  (24000, 256)\n",
      "y shape:  (24000,)\n"
     ]
    }
   ],
   "source": [
    "X = np.array([x for x in df[\"byte_bfh\"]])\n",
    "y = np.array([y for y in df[\"class\"]])\n",
    "\n",
    "print(\"X shape: \", X.shape)\n",
    "print(\"y shape: \", y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# we use the same split ratio 70% training\n",
    "X_train, X_temp, y_train, y_temp = train_test_split(X, y, test_size=0.3, random_state=42)\n",
    "# 15% validation and 15% test\n",
    "X_val, X_test, y_val, y_test = train_test_split(X_temp, y_temp, test_size=0.5, random_state=42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X training shape:  (16800, 256)\n",
      "X validation shape:  (3600, 256)\n",
      "X testing shape:  (3600, 256) \n",
      "\n",
      "y training shape:  (16800,)\n",
      "y validation shape:  (3600,)\n",
      "y testing shape:  (3600,)\n"
     ]
    }
   ],
   "source": [
    "print(\"X training shape: \", X_train.shape)\n",
    "print(\"X validation shape: \", X_val.shape)\n",
    "print(\"X testing shape: \", X_test.shape, \"\\n\")\n",
    "print(\"y training shape: \", y_train.shape)\n",
    "print(\"y validation shape: \", y_val.shape)\n",
    "print(\"y testing shape: \", y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Models Training and Evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feed Forward Neural Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### a. Base FFNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ dense (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)       │           <span style=\"color: #00af00; text-decoration-color: #00af00\">512</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)       │        <span style=\"color: #00af00; text-decoration-color: #00af00\">32,896</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32768</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │       <span style=\"color: #00af00; text-decoration-color: #00af00\">425,997</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ dense (\u001b[38;5;33mDense\u001b[0m)                   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m256\u001b[0m)       │           \u001b[38;5;34m512\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_1 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m128\u001b[0m)       │        \u001b[38;5;34m32,896\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten (\u001b[38;5;33mFlatten\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m32768\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_2 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │       \u001b[38;5;34m425,997\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">459,405</span> (1.75 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m459,405\u001b[0m (1.75 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">459,405</span> (1.75 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m459,405\u001b[0m (1.75 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn = Ffnn(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m13s\u001b[0m 23ms/step - accuracy: 0.7596 - loss: 1.2804 - val_accuracy: 0.9014 - val_loss: 0.3624\n",
      "Epoch 2/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 21ms/step - accuracy: 0.9071 - loss: 0.3075 - val_accuracy: 0.9153 - val_loss: 0.3278\n",
      "Epoch 3/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m12s\u001b[0m 24ms/step - accuracy: 0.9189 - loss: 0.2812 - val_accuracy: 0.9183 - val_loss: 0.3322\n",
      "Epoch 4/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m13s\u001b[0m 24ms/step - accuracy: 0.9329 - loss: 0.2303 - val_accuracy: 0.9239 - val_loss: 0.3215\n"
     ]
    }
   ],
   "source": [
    "ffnn_pred = ffnn.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=4,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m113/113\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 9ms/step\n"
     ]
    }
   ],
   "source": [
    "ffnn_pred = ffnn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feed Forward Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.9147222222222222.\n",
      "precision\t0.9161491319206783.\n",
      "recall\t\t0.9160609052137275.\n",
      "f1-score\t0.9149543264423364.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, ffnn_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{ffnn.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.97      1.00      0.99       287\n",
      "         pdf       0.95      0.94      0.94       317\n",
      "          ps       0.99      0.97      0.98       287\n",
      "         xls       0.99      0.98      0.99       304\n",
      "         ppt       0.83      0.93      0.88       307\n",
      "         swf       0.85      0.71      0.77       307\n",
      "         gif       0.86      0.96      0.91       308\n",
      "         jpg       0.89      0.86      0.87       295\n",
      "         png       0.79      0.75      0.77       311\n",
      "        html       0.94      0.97      0.95       303\n",
      "         txt       0.97      0.98      0.97       285\n",
      "         xml       0.96      0.95      0.96       289\n",
      "\n",
      "    accuracy                           0.91      3600\n",
      "   macro avg       0.92      0.92      0.91      3600\n",
      "weighted avg       0.91      0.91      0.91      3600\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ffnn_report = classification_report(y_test, ffnn_pred, target_names=CLASS_NAMES)\n",
    "print(ffnn_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn_cm = confusion_matrix(y_test, ffnn_pred)\n",
    "plot_confusion_matrix(ffnn_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### b. Fine-Tuned FFNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ dense_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">352</span>)       │           <span style=\"color: #00af00; text-decoration-color: #00af00\">704</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_4 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">32</span>)        │        <span style=\"color: #00af00; text-decoration-color: #00af00\">11,296</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">8192</span>)           │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_5 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │       <span style=\"color: #00af00; text-decoration-color: #00af00\">106,509</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ dense_3 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m352\u001b[0m)       │           \u001b[38;5;34m704\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_4 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m, \u001b[38;5;34m32\u001b[0m)        │        \u001b[38;5;34m11,296\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_1 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m8192\u001b[0m)           │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_5 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │       \u001b[38;5;34m106,509\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">118,509</span> (462.93 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m118,509\u001b[0m (462.93 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">118,509</span> (462.93 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m118,509\u001b[0m (462.93 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn2 = Ffnn2(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 19ms/step - accuracy: 0.7490 - loss: 0.8810 - val_accuracy: 0.8431 - val_loss: 0.4991\n",
      "Epoch 2/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 18ms/step - accuracy: 0.9087 - loss: 0.3070 - val_accuracy: 0.9200 - val_loss: 0.3042\n",
      "Epoch 3/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 17ms/step - accuracy: 0.9233 - loss: 0.2619 - val_accuracy: 0.9131 - val_loss: 0.3238\n",
      "Epoch 4/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 18ms/step - accuracy: 0.9358 - loss: 0.2157 - val_accuracy: 0.9283 - val_loss: 0.2871\n"
     ]
    }
   ],
   "source": [
    "ffnn2_history = ffnn2.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=4,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn2.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m113/113\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 9ms/step\n"
     ]
    }
   ],
   "source": [
    "ffnn2_pred = ffnn2.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feed Forward Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.9222222222222223.\n",
      "precision\t0.9303855786646386.\n",
      "recall\t\t0.9237800119739349.\n",
      "f1-score\t0.9241574659680206.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, ffnn2_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{ffnn2.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.98      1.00      0.99       287\n",
      "         pdf       1.00      0.92      0.96       317\n",
      "          ps       1.00      0.98      0.99       287\n",
      "         xls       0.99      0.99      0.99       304\n",
      "         ppt       0.93      0.90      0.91       307\n",
      "         swf       0.67      0.90      0.76       307\n",
      "         gif       0.94      0.94      0.94       308\n",
      "         jpg       0.89      0.89      0.89       295\n",
      "         png       0.90      0.67      0.77       311\n",
      "        html       0.96      0.95      0.96       303\n",
      "         txt       0.98      0.99      0.98       285\n",
      "         xml       0.95      0.97      0.96       289\n",
      "\n",
      "    accuracy                           0.92      3600\n",
      "   macro avg       0.93      0.92      0.92      3600\n",
      "weighted avg       0.93      0.92      0.92      3600\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ffnn2_report = classification_report(y_test, ffnn2_pred, target_names=CLASS_NAMES)\n",
    "print(ffnn2_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ffnn2_cm = confusion_matrix(y_test, ffnn2_pred)\n",
    "plot_confusion_matrix(ffnn2_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Convolutional Neural Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### a. Base CNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_2\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_2\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv1d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">254</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)    │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">127</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv1d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">125</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)       │        <span style=\"color: #00af00; text-decoration-color: #00af00\">24,704</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">62</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">128</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">7936</span>)           │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_6 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │       <span style=\"color: #00af00; text-decoration-color: #00af00\">103,181</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv1d (\u001b[38;5;33mConv1D\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m254\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │           \u001b[38;5;34m256\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d (\u001b[38;5;33mMaxPooling1D\u001b[0m)    │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m127\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv1d_1 (\u001b[38;5;33mConv1D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m125\u001b[0m, \u001b[38;5;34m128\u001b[0m)       │        \u001b[38;5;34m24,704\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_1 (\u001b[38;5;33mMaxPooling1D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m62\u001b[0m, \u001b[38;5;34m128\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_2 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m7936\u001b[0m)           │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_6 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │       \u001b[38;5;34m103,181\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">128,141</span> (500.55 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m128,141\u001b[0m (500.55 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">128,141</span> (500.55 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m128,141\u001b[0m (500.55 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn = Cnn(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m7s\u001b[0m 12ms/step - accuracy: 0.6853 - loss: 1.8907 - val_accuracy: 0.8583 - val_loss: 0.4889\n",
      "Epoch 2/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 11ms/step - accuracy: 0.8707 - loss: 0.4007 - val_accuracy: 0.8647 - val_loss: 0.4249\n",
      "Epoch 3/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 10ms/step - accuracy: 0.8970 - loss: 0.3121 - val_accuracy: 0.8994 - val_loss: 0.3646\n",
      "Epoch 4/4\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 11ms/step - accuracy: 0.9172 - loss: 0.2533 - val_accuracy: 0.8836 - val_loss: 0.3735\n"
     ]
    }
   ],
   "source": [
    "cnn_history = cnn.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=4,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m113/113\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 6ms/step\n"
     ]
    }
   ],
   "source": [
    "cnn_pred = cnn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Convolutional Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.89.\n",
      "precision\t0.9021026936858277.\n",
      "recall\t\t0.8917994201551163.\n",
      "f1-score\t0.8919011803993846.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, cnn_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{cnn.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.98      0.99      0.99       287\n",
      "         pdf       0.98      0.94      0.96       317\n",
      "          ps       1.00      0.97      0.98       287\n",
      "         xls       1.00      0.98      0.99       304\n",
      "         ppt       0.81      0.60      0.69       307\n",
      "         swf       0.62      0.92      0.74       307\n",
      "         gif       0.96      0.91      0.94       308\n",
      "         jpg       0.79      0.88      0.83       295\n",
      "         png       0.87      0.69      0.77       311\n",
      "        html       0.93      0.93      0.93       303\n",
      "         txt       0.94      0.98      0.96       285\n",
      "         xml       0.95      0.92      0.93       289\n",
      "\n",
      "    accuracy                           0.89      3600\n",
      "   macro avg       0.90      0.89      0.89      3600\n",
      "weighted avg       0.90      0.89      0.89      3600\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cnn_report = classification_report(y_test, cnn_pred, target_names=CLASS_NAMES)\n",
    "print(cnn_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn_cm = confusion_matrix(y_test, cnn_pred)\n",
    "plot_confusion_matrix(cnn_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### b. Fine-Tuned CNN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_3\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_3\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv1d_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">254</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │           <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_2 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">127</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">64</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv1d_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Conv1D</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">125</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">192</span>)       │        <span style=\"color: #00af00; text-decoration-color: #00af00\">37,056</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">MaxPooling1D</span>)  │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">62</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">192</span>)        │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Flatten</span>)             │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">11904</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)               │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">11904</span>)          │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_7 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">256</span>)            │     <span style=\"color: #00af00; text-decoration-color: #00af00\">3,047,680</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_8 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">3,341</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ conv1d_2 (\u001b[38;5;33mConv1D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m254\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │           \u001b[38;5;34m256\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_2 (\u001b[38;5;33mMaxPooling1D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m127\u001b[0m, \u001b[38;5;34m64\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ conv1d_3 (\u001b[38;5;33mConv1D\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m125\u001b[0m, \u001b[38;5;34m192\u001b[0m)       │        \u001b[38;5;34m37,056\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ max_pooling1d_3 (\u001b[38;5;33mMaxPooling1D\u001b[0m)  │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m62\u001b[0m, \u001b[38;5;34m192\u001b[0m)        │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ flatten_3 (\u001b[38;5;33mFlatten\u001b[0m)             │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m11904\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dropout (\u001b[38;5;33mDropout\u001b[0m)               │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m11904\u001b[0m)          │             \u001b[38;5;34m0\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_7 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m256\u001b[0m)            │     \u001b[38;5;34m3,047,680\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_8 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │         \u001b[38;5;34m3,341\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">3,088,333</span> (11.78 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m3,088,333\u001b[0m (11.78 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">3,088,333</span> (11.78 MB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m3,088,333\u001b[0m (11.78 MB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn2 = Cnn2(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m25s\u001b[0m 43ms/step - accuracy: 0.6680 - loss: 1.9925 - val_accuracy: 0.8553 - val_loss: 0.4280\n",
      "Epoch 2/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m22s\u001b[0m 42ms/step - accuracy: 0.8675 - loss: 0.4108 - val_accuracy: 0.8967 - val_loss: 0.3248\n",
      "Epoch 3/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m22s\u001b[0m 41ms/step - accuracy: 0.8978 - loss: 0.3167 - val_accuracy: 0.9014 - val_loss: 0.2997\n",
      "Epoch 4/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m22s\u001b[0m 43ms/step - accuracy: 0.9163 - loss: 0.2510 - val_accuracy: 0.9175 - val_loss: 0.2809\n",
      "Epoch 5/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m23s\u001b[0m 44ms/step - accuracy: 0.9294 - loss: 0.2223 - val_accuracy: 0.9228 - val_loss: 0.2539\n",
      "Epoch 6/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m23s\u001b[0m 44ms/step - accuracy: 0.9434 - loss: 0.1728 - val_accuracy: 0.9186 - val_loss: 0.2499\n",
      "Epoch 7/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m22s\u001b[0m 43ms/step - accuracy: 0.9453 - loss: 0.1567 - val_accuracy: 0.9208 - val_loss: 0.2588\n",
      "Epoch 8/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m23s\u001b[0m 43ms/step - accuracy: 0.9530 - loss: 0.1424 - val_accuracy: 0.9158 - val_loss: 0.2607\n",
      "Epoch 9/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m23s\u001b[0m 43ms/step - accuracy: 0.9619 - loss: 0.1101 - val_accuracy: 0.9339 - val_loss: 0.2554\n",
      "Epoch 10/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m23s\u001b[0m 43ms/step - accuracy: 0.9695 - loss: 0.0976 - val_accuracy: 0.9314 - val_loss: 0.2461\n"
     ]
    }
   ],
   "source": [
    "cnn2_history = cnn2.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=10,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn2.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m113/113\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 8ms/step\n"
     ]
    }
   ],
   "source": [
    "cnn2_pred = cnn2.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Convolutional Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.9313888888888889.\n",
      "precision\t0.9332538798288691.\n",
      "recall\t\t0.9322479980273095.\n",
      "f1-score\t0.9322164396866834.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, cnn2_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{cnn2.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.99      0.99      0.99       287\n",
      "         pdf       0.98      0.94      0.96       317\n",
      "          ps       0.96      0.98      0.97       287\n",
      "         xls       0.99      0.97      0.98       304\n",
      "         ppt       0.83      0.84      0.84       307\n",
      "         swf       0.90      0.90      0.90       307\n",
      "         gif       0.97      0.96      0.97       308\n",
      "         jpg       0.83      0.96      0.89       295\n",
      "         png       0.88      0.83      0.86       311\n",
      "        html       0.96      0.93      0.95       303\n",
      "         txt       0.93      0.95      0.94       285\n",
      "         xml       0.97      0.94      0.95       289\n",
      "\n",
      "    accuracy                           0.93      3600\n",
      "   macro avg       0.93      0.93      0.93      3600\n",
      "weighted avg       0.93      0.93      0.93      3600\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cnn2_report = classification_report(y_test, cnn2_pred, target_names=CLASS_NAMES)\n",
    "print(cnn2_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cnn2_cm = confusion_matrix(y_test, cnn2_pred)\n",
    "plot_confusion_matrix(cnn2_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Gated Reccurent Unit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_4\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_4\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ bidirectional (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Bidirectional</span>)   │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">136</span>)            │        <span style=\"color: #00af00; text-decoration-color: #00af00\">28,968</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_9 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,781</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ bidirectional (\u001b[38;5;33mBidirectional\u001b[0m)   │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m136\u001b[0m)            │        \u001b[38;5;34m28,968\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_9 (\u001b[38;5;33mDense\u001b[0m)                 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │         \u001b[38;5;34m1,781\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">30,749</span> (120.11 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m30,749\u001b[0m (120.11 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">30,749</span> (120.11 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m30,749\u001b[0m (120.11 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gru = Gru(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m63s\u001b[0m 115ms/step - accuracy: 0.4740 - loss: 1.4693 - val_accuracy: 0.6531 - val_loss: 0.8537\n",
      "Epoch 2/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m60s\u001b[0m 114ms/step - accuracy: 0.7347 - loss: 0.7362 - val_accuracy: 0.8217 - val_loss: 0.5531\n",
      "Epoch 3/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m57s\u001b[0m 109ms/step - accuracy: 0.8372 - loss: 0.4940 - val_accuracy: 0.8603 - val_loss: 0.4340\n",
      "Epoch 4/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m59s\u001b[0m 112ms/step - accuracy: 0.8701 - loss: 0.4210 - val_accuracy: 0.8072 - val_loss: 0.5982\n",
      "Epoch 5/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m61s\u001b[0m 116ms/step - accuracy: 0.8482 - loss: 0.4668 - val_accuracy: 0.8281 - val_loss: 0.5181\n",
      "Epoch 6/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m60s\u001b[0m 115ms/step - accuracy: 0.8428 - loss: 0.4771 - val_accuracy: 0.8569 - val_loss: 0.4357\n",
      "Epoch 7/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m61s\u001b[0m 116ms/step - accuracy: 0.8616 - loss: 0.4226 - val_accuracy: 0.8569 - val_loss: 0.4480\n",
      "Epoch 8/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m60s\u001b[0m 114ms/step - accuracy: 0.8670 - loss: 0.4188 - val_accuracy: 0.8422 - val_loss: 0.4668\n",
      "Epoch 9/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m61s\u001b[0m 116ms/step - accuracy: 0.8621 - loss: 0.4245 - val_accuracy: 0.8772 - val_loss: 0.4076\n",
      "Epoch 10/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m61s\u001b[0m 116ms/step - accuracy: 0.8806 - loss: 0.3827 - val_accuracy: 0.8883 - val_loss: 0.3842\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x1d359d6d1c0>"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gru.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=10,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gru.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m113/113\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 43ms/step\n"
     ]
    }
   ],
   "source": [
    "gru_pred = gru.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gated Reccurent Unit performance evaluation:\n",
      "\n",
      "accuracy\t0.8702777777777778.\n",
      "precision\t0.8733228474249511.\n",
      "recall\t\t0.8716358252770902.\n",
      "f1-score\t0.8716699518032752.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, gru_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{gru.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.97      0.99      0.98       287\n",
      "         pdf       0.93      0.85      0.89       317\n",
      "          ps       0.98      0.98      0.98       287\n",
      "         xls       0.94      0.92      0.93       304\n",
      "         ppt       0.86      0.87      0.86       307\n",
      "         swf       0.72      0.77      0.75       307\n",
      "         gif       0.90      0.78      0.83       308\n",
      "         jpg       0.84      0.87      0.85       295\n",
      "         png       0.79      0.84      0.81       311\n",
      "        html       0.84      0.86      0.85       303\n",
      "         txt       0.83      0.91      0.87       285\n",
      "         xml       0.88      0.83      0.86       289\n",
      "\n",
      "    accuracy                           0.87      3600\n",
      "   macro avg       0.87      0.87      0.87      3600\n",
      "weighted avg       0.87      0.87      0.87      3600\n",
      "\n"
     ]
    }
   ],
   "source": [
    "gru_report = classification_report(y_test, gru_pred, target_names=CLASS_NAMES)\n",
    "print(gru_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "gru_cm = confusion_matrix(y_test, gru_pred)\n",
    "plot_confusion_matrix(gru_cm, CLASS_NAMES)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Long Short-Term Memory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_5\"</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1mModel: \"sequential_5\"\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ bidirectional_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Bidirectional</span>) │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">136</span>)            │        <span style=\"color: #00af00; text-decoration-color: #00af00\">38,080</span> │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_10 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                │ (<span style=\"color: #00d7ff; text-decoration-color: #00d7ff\">None</span>, <span style=\"color: #00af00; text-decoration-color: #00af00\">13</span>)             │         <span style=\"color: #00af00; text-decoration-color: #00af00\">1,781</span> │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "</pre>\n"
      ],
      "text/plain": [
       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ bidirectional_1 (\u001b[38;5;33mBidirectional\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m136\u001b[0m)            │        \u001b[38;5;34m38,080\u001b[0m │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_10 (\u001b[38;5;33mDense\u001b[0m)                │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m13\u001b[0m)             │         \u001b[38;5;34m1,781\u001b[0m │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">39,861</span> (155.71 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m39,861\u001b[0m (155.71 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">39,861</span> (155.71 KB)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m39,861\u001b[0m (155.71 KB)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lstm = Lstm(timesteps=256, features=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m52s\u001b[0m 93ms/step - accuracy: 0.5088 - loss: 1.4080 - val_accuracy: 0.6236 - val_loss: 0.9321\n",
      "Epoch 2/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m35s\u001b[0m 66ms/step - accuracy: 0.7116 - loss: 0.7813 - val_accuracy: 0.7883 - val_loss: 0.6259\n",
      "Epoch 3/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m33s\u001b[0m 63ms/step - accuracy: 0.7971 - loss: 0.5822 - val_accuracy: 0.8253 - val_loss: 0.5321\n",
      "Epoch 4/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m37s\u001b[0m 71ms/step - accuracy: 0.8351 - loss: 0.4926 - val_accuracy: 0.8428 - val_loss: 0.4688\n",
      "Epoch 5/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m41s\u001b[0m 78ms/step - accuracy: 0.8497 - loss: 0.4538 - val_accuracy: 0.8614 - val_loss: 0.4281\n",
      "Epoch 6/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m39s\u001b[0m 75ms/step - accuracy: 0.8682 - loss: 0.4191 - val_accuracy: 0.8694 - val_loss: 0.4010\n",
      "Epoch 7/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m46s\u001b[0m 87ms/step - accuracy: 0.8688 - loss: 0.3994 - val_accuracy: 0.8697 - val_loss: 0.3995\n",
      "Epoch 8/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m49s\u001b[0m 94ms/step - accuracy: 0.8753 - loss: 0.3793 - val_accuracy: 0.8700 - val_loss: 0.4005\n",
      "Epoch 9/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m36s\u001b[0m 69ms/step - accuracy: 0.8837 - loss: 0.3585 - val_accuracy: 0.8858 - val_loss: 0.3453\n",
      "Epoch 10/10\n",
      "\u001b[1m525/525\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m42s\u001b[0m 81ms/step - accuracy: 0.8886 - loss: 0.3379 - val_accuracy: 0.8883 - val_loss: 0.3410\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x1d357ee8500>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lstm.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=10,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lstm.plot_learning_curves()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m113/113\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 41ms/step\n"
     ]
    }
   ],
   "source": [
    "lstm_pred = lstm.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Long Short-Term Memory performance evaluation:\n",
      "\n",
      "accuracy\t0.8836111111111111.\n",
      "precision\t0.8882065481369453.\n",
      "recall\t\t0.8849370696917886.\n",
      "f1-score\t0.8847797186718659.\n"
     ]
    }
   ],
   "source": [
    "metrics = evaluate_performance(y_test, lstm_pred)\n",
    "accuracy, precision, recall, f1 = metrics[\"accuracy\"], metrics[\"precision\"], metrics[\"recall\"], metrics[\"f1_score\"]\n",
    "print(f\"\"\"{lstm.name} performance evaluation:\\n\\naccuracy\\t{accuracy}.\\n\\\n",
    "precision\\t{precision}.\\nrecall\\t\\t{recall}.\\nf1-score\\t{f1}.\"\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.97      0.98      0.97       287\n",
      "         pdf       0.96      0.87      0.91       317\n",
      "          ps       0.99      0.94      0.96       287\n",
      "         xls       0.99      0.96      0.98       304\n",
      "         ppt       0.89      0.88      0.88       307\n",
      "         swf       0.79      0.79      0.79       307\n",
      "         gif       0.94      0.88      0.91       308\n",
      "         jpg       0.75      0.94      0.84       295\n",
      "         png       0.85      0.79      0.82       311\n",
      "        html       0.88      0.79      0.83       303\n",
      "         txt       0.85      0.91      0.88       285\n",
      "         xml       0.81      0.90      0.85       289\n",
      "\n",
      "    accuracy                           0.88      3600\n",
      "   macro avg       0.89      0.88      0.88      3600\n",
      "weighted avg       0.89      0.88      0.88      3600\n",
      "\n"
     ]
    }
   ],
   "source": [
    "lstm_report = classification_report(y_test, lstm_pred, target_names=CLASS_NAMES)\n",
    "print(lstm_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lstm_cm = confusion_matrix(y_test, lstm_pred)\n",
    "plot_confusion_matrix(lstm_cm, CLASS_NAMES)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv",
   "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": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}