system4.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Experiments 4:\n",
    "### generating byte frequency distributions derived from file body 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_2nd_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"
   ]
  },
  {
   "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": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The average file size is: 519.8767892054933\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": 4,
   "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": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "type\n",
       "pdf     168373\n",
       "html    110537\n",
       "doc      52927\n",
       "xls      45050\n",
       "txt      42195\n",
       "jpg      41034\n",
       "ppt      39412\n",
       "xml      13837\n",
       "ps       12275\n",
       "gif       8412\n",
       "swf       2694\n",
       "png       1356\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# we sample files whose size is larger than 16 kb\n",
    "# this is to ensure we have 2 body blocks at least\n",
    "df = df[df['type'].isin(CLASS_NAMES)]\n",
    "df = df[df['size KB'] > 16]\n",
    "df['type'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\User\\AppData\\Local\\Temp\\ipykernel_19220\\3309657051.py:2: 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(\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "type\n",
       "doc     2000\n",
       "gif     2000\n",
       "html    2000\n",
       "jpg     2000\n",
       "pdf     2000\n",
       "ppt     2000\n",
       "ps      2000\n",
       "swf     2000\n",
       "txt     2000\n",
       "xls     2000\n",
       "xml     2000\n",
       "png     1356\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# sample 12 file types\n",
    "df = df.groupby('type').apply(\n",
    "    lambda x: x if x.name == \"png\" else x.sample(n=min(len(x), 2000), random_state=42)\n",
    ").reset_index(drop=True)\n",
    "\n",
    "df[\"type\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_dir = os.path.join(os.getcwd(), \"govdocs1\")\n",
    "df[\"body_block_bytes\"] = df[\"file\"].apply(lambda file: get_2nd_block_bytes(os.path.join(base_dir, file)))\n",
    "df[\"byte_integers\"] = df[\"body_block_bytes\"].apply(lambda byte_sequences: 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        4096\n",
      "1        4096\n",
      "2        4096\n",
      "3        4096\n",
      "4        4096\n",
      "         ... \n",
      "23351    4096\n",
      "23352    4096\n",
      "23353    4096\n",
      "23354    4096\n",
      "23355    4096\n",
      "Name: byte_integers, Length: 23356, dtype: int64\n",
      "all byte sequences of the same length: True\n"
     ]
    }
   ],
   "source": [
    "byte_lengths = df[\"byte_integers\"].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": [
    {
     "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>file</th>\n",
       "      <th>type</th>\n",
       "      <th>size KB</th>\n",
       "      <th>body_block_bytes</th>\n",
       "      <th>byte_integers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>459548.doc</td>\n",
       "      <td>doc</td>\n",
       "      <td>390.5</td>\n",
       "      <td>b'n where (which folder) this is before you le...</td>\n",
       "      <td>[110, 32, 119, 104, 101, 114, 101, 32, 40, 119...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>609183.doc</td>\n",
       "      <td>doc</td>\n",
       "      <td>86.5</td>\n",
       "      <td>b' MERGEFORMAT \\x14\\x08\\x01\\x15\\r2008 BNL Scie...</td>\n",
       "      <td>[32, 77, 69, 82, 71, 69, 70, 79, 82, 77, 65, 8...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>284373.doc</td>\n",
       "      <td>doc</td>\n",
       "      <td>61.0</td>\n",
       "      <td>b\"649\\x96656. \\rAhluwalia IB, Tessaro I, Grumm...</td>\n",
       "      <td>[54, 52, 57, 150, 54, 53, 54, 46, 32, 13, 65, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>010461.doc</td>\n",
       "      <td>doc</td>\n",
       "      <td>129.5</td>\n",
       "      <td>b' more thorough understanding of auction outc...</td>\n",
       "      <td>[32, 109, 111, 114, 101, 32, 116, 104, 111, 11...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>430917.doc</td>\n",
       "      <td>doc</td>\n",
       "      <td>58.0</td>\n",
       "      <td>b' Now, it became clear that most of the decis...</td>\n",
       "      <td>[32, 78, 111, 119, 44, 32, 105, 116, 32, 98, 1...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         file type  size KB  \\\n",
       "0  459548.doc  doc    390.5   \n",
       "1  609183.doc  doc     86.5   \n",
       "2  284373.doc  doc     61.0   \n",
       "3  010461.doc  doc    129.5   \n",
       "4  430917.doc  doc     58.0   \n",
       "\n",
       "                                    body_block_bytes  \\\n",
       "0  b'n where (which folder) this is before you le...   \n",
       "1  b' MERGEFORMAT \\x14\\x08\\x01\\x15\\r2008 BNL Scie...   \n",
       "2  b\"649\\x96656. \\rAhluwalia IB, Tessaro I, Grumm...   \n",
       "3  b' more thorough understanding of auction outc...   \n",
       "4  b' Now, it became clear that most of the decis...   \n",
       "\n",
       "                                       byte_integers  \n",
       "0  [110, 32, 119, 104, 101, 114, 101, 32, 40, 119...  \n",
       "1  [32, 77, 69, 82, 71, 69, 70, 79, 82, 77, 65, 8...  \n",
       "2  [54, 52, 57, 150, 54, 53, 54, 46, 32, 13, 65, ...  \n",
       "3  [32, 109, 111, 114, 101, 32, 116, 104, 111, 11...  \n",
       "4  [32, 78, 111, 119, 44, 32, 105, 116, 32, 98, 1...  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"byte_bfh\"] = df[\"byte_integers\"].apply(lambda byte_integers: byte_frequency_histogram(byte_integers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0        256\n",
       "1        256\n",
       "2        256\n",
       "3        256\n",
       "4        256\n",
       "        ... \n",
       "23351    256\n",
       "23352    256\n",
       "23353    256\n",
       "23354    256\n",
       "23355    256\n",
       "Name: byte_bfh, Length: 23356, dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"byte_bfh\"].apply(len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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",
       "        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>file</th>\n",
       "      <th>type</th>\n",
       "      <th>size KB</th>\n",
       "      <th>body_block_bytes</th>\n",
       "      <th>byte_integers</th>\n",
       "      <th>byte_bfh</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8111</th>\n",
       "      <td>254817.pdf</td>\n",
       "      <td>pdf</td>\n",
       "      <td>24.717773</td>\n",
       "      <td>b'\\xcag\\xc9\\x8fb\\x88q!Z\\xf9)\\xf8m\\xd0\\xd7EYp7u...</td>\n",
       "      <td>[202, 103, 201, 143, 98, 136, 113, 33, 90, 249...</td>\n",
       "      <td>[16, 14, 19, 12, 8, 8, 14, 15, 16, 13, 9, 17, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9790</th>\n",
       "      <td>552495.pdf</td>\n",
       "      <td>pdf</td>\n",
       "      <td>4201.428711</td>\n",
       "      <td>b'\\xae\\xcb\\xfdag\\xc9\\x17\\xe7\\xe9\\xb5m\\xfac\\xff...</td>\n",
       "      <td>[174, 203, 253, 97, 103, 201, 23, 231, 233, 18...</td>\n",
       "      <td>[50, 33, 22, 15, 15, 23, 18, 24, 26, 17, 25, 1...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17079</th>\n",
       "      <td>655055.swf</td>\n",
       "      <td>swf</td>\n",
       "      <td>41.819336</td>\n",
       "      <td>b'\\xea\\x16\\n\\x84kDP\\x17\\xa9V8-\\xacZ`^\\xa5\\xb8\\...</td>\n",
       "      <td>[234, 22, 10, 132, 107, 68, 80, 23, 169, 86, 5...</td>\n",
       "      <td>[317, 60, 17, 8, 35, 13, 29, 16, 27, 16, 13, 3...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21740</th>\n",
       "      <td>708641.xml</td>\n",
       "      <td>xml</td>\n",
       "      <td>1051.511719</td>\n",
       "      <td>b'nt Detail\"&gt;http://www.gpo.gov/fdsys/granule/...</td>\n",
       "      <td>[110, 116, 32, 68, 101, 116, 97, 105, 108, 34,...</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 94, 0, 0, 0, 0,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7834</th>\n",
       "      <td>735765.jpg</td>\n",
       "      <td>jpg</td>\n",
       "      <td>23.819336</td>\n",
       "      <td>b'u\\x9b`\\xaf\\xfb\\xb9\\x93;$Q\\xc8\\xff\\x00\\x11^7\\...</td>\n",
       "      <td>[117, 155, 96, 175, 251, 185, 147, 59, 36, 81,...</td>\n",
       "      <td>[104, 26, 42, 41, 28, 43, 18, 32, 17, 8, 19, 9...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             file type      size KB  \\\n",
       "8111   254817.pdf  pdf    24.717773   \n",
       "9790   552495.pdf  pdf  4201.428711   \n",
       "17079  655055.swf  swf    41.819336   \n",
       "21740  708641.xml  xml  1051.511719   \n",
       "7834   735765.jpg  jpg    23.819336   \n",
       "\n",
       "                                        body_block_bytes  \\\n",
       "8111   b'\\xcag\\xc9\\x8fb\\x88q!Z\\xf9)\\xf8m\\xd0\\xd7EYp7u...   \n",
       "9790   b'\\xae\\xcb\\xfdag\\xc9\\x17\\xe7\\xe9\\xb5m\\xfac\\xff...   \n",
       "17079  b'\\xea\\x16\\n\\x84kDP\\x17\\xa9V8-\\xacZ`^\\xa5\\xb8\\...   \n",
       "21740  b'nt Detail\">http://www.gpo.gov/fdsys/granule/...   \n",
       "7834   b'u\\x9b`\\xaf\\xfb\\xb9\\x93;$Q\\xc8\\xff\\x00\\x11^7\\...   \n",
       "\n",
       "                                           byte_integers  \\\n",
       "8111   [202, 103, 201, 143, 98, 136, 113, 33, 90, 249...   \n",
       "9790   [174, 203, 253, 97, 103, 201, 23, 231, 233, 18...   \n",
       "17079  [234, 22, 10, 132, 107, 68, 80, 23, 169, 86, 5...   \n",
       "21740  [110, 116, 32, 68, 101, 116, 97, 105, 108, 34,...   \n",
       "7834   [117, 155, 96, 175, 251, 185, 147, 59, 36, 81,...   \n",
       "\n",
       "                                                byte_bfh  \n",
       "8111   [16, 14, 19, 12, 8, 8, 14, 15, 16, 13, 9, 17, ...  \n",
       "9790   [50, 33, 22, 15, 15, 23, 18, 24, 26, 17, 25, 1...  \n",
       "17079  [317, 60, 17, 8, 35, 13, 29, 16, 27, 16, 13, 3...  \n",
       "21740  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 94, 0, 0, 0, 0,...  \n",
       "7834   [104, 26, 42, 41, 28, 43, 18, 32, 17, 8, 19, 9...  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(n=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"class\"] = df[\"type\"].apply(lambda file_type: convert_cat2num(file_type))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "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",
       "        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>file</th>\n",
       "      <th>type</th>\n",
       "      <th>size KB</th>\n",
       "      <th>body_block_bytes</th>\n",
       "      <th>byte_integers</th>\n",
       "      <th>byte_bfh</th>\n",
       "      <th>class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8357</th>\n",
       "      <td>528205.pdf</td>\n",
       "      <td>pdf</td>\n",
       "      <td>309.973633</td>\n",
       "      <td>b'\\xbfD\\\\~}L\\x9d\\x1bwa\\xa1a\\x18\\xecZL\\xdbT\\xbd...</td>\n",
       "      <td>[191, 68, 92, 126, 125, 76, 157, 27, 119, 97, ...</td>\n",
       "      <td>[9, 16, 16, 22, 20, 16, 16, 19, 14, 20, 37, 15...</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18077</th>\n",
       "      <td>014534.txt</td>\n",
       "      <td>txt</td>\n",
       "      <td>1527.963867</td>\n",
       "      <td>b'pha virginica L.                            ...</td>\n",
       "      <td>[112, 104, 97, 32, 118, 105, 114, 103, 105, 11...</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 19, 0, 0, 19, 0...</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12481</th>\n",
       "      <td>093144.ppt</td>\n",
       "      <td>ppt</td>\n",
       "      <td>2654.000000</td>\n",
       "      <td>b']\\xc6\\x1cOn7:\\xa8\\xe4`\\xe0\\x92~\\xbcc\\xb5YZ\\x...</td>\n",
       "      <td>[93, 198, 28, 79, 110, 55, 58, 168, 228, 96, 2...</td>\n",
       "      <td>[36, 19, 8, 28, 17, 19, 22, 22, 10, 13, 19, 14...</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5288</th>\n",
       "      <td>649742.html</td>\n",
       "      <td>html</td>\n",
       "      <td>20.818359</td>\n",
       "      <td>b'0;&amp;#160;&amp;#160;&amp;#160;&amp;#160;&lt;/span&gt;The Sixth C...</td>\n",
       "      <td>[48, 59, 38, 35, 49, 54, 48, 59, 38, 35, 49, 5...</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 43, 0, 0, 43, 0...</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5826</th>\n",
       "      <td>213078.html</td>\n",
       "      <td>html</td>\n",
       "      <td>17.566406</td>\n",
       "      <td>b'ear\" &gt;&lt;br&gt;Mostly&lt;br&gt;Clear&lt;br&gt;Lo &lt;font color=...</td>\n",
       "      <td>[101, 97, 114, 34, 32, 62, 60, 98, 114, 62, 77...</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 0, 0, 0, 0,...</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              file  type      size KB  \\\n",
       "8357    528205.pdf   pdf   309.973633   \n",
       "18077   014534.txt   txt  1527.963867   \n",
       "12481   093144.ppt   ppt  2654.000000   \n",
       "5288   649742.html  html    20.818359   \n",
       "5826   213078.html  html    17.566406   \n",
       "\n",
       "                                        body_block_bytes  \\\n",
       "8357   b'\\xbfD\\\\~}L\\x9d\\x1bwa\\xa1a\\x18\\xecZL\\xdbT\\xbd...   \n",
       "18077  b'pha virginica L.                            ...   \n",
       "12481  b']\\xc6\\x1cOn7:\\xa8\\xe4`\\xe0\\x92~\\xbcc\\xb5YZ\\x...   \n",
       "5288   b'0;&#160;&#160;&#160;&#160;</span>The Sixth C...   \n",
       "5826   b'ear\" ><br>Mostly<br>Clear<br>Lo <font color=...   \n",
       "\n",
       "                                           byte_integers  \\\n",
       "8357   [191, 68, 92, 126, 125, 76, 157, 27, 119, 97, ...   \n",
       "18077  [112, 104, 97, 32, 118, 105, 114, 103, 105, 11...   \n",
       "12481  [93, 198, 28, 79, 110, 55, 58, 168, 228, 96, 2...   \n",
       "5288   [48, 59, 38, 35, 49, 54, 48, 59, 38, 35, 49, 5...   \n",
       "5826   [101, 97, 114, 34, 32, 62, 60, 98, 114, 62, 77...   \n",
       "\n",
       "                                                byte_bfh  class  \n",
       "8357   [9, 16, 16, 22, 20, 16, 16, 19, 14, 20, 37, 15...      2  \n",
       "18077  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 19, 0, 0, 19, 0...     11  \n",
       "12481  [36, 19, 8, 28, 17, 19, 22, 22, 10, 13, 19, 14...      5  \n",
       "5288   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 43, 0, 0, 43, 0...     10  \n",
       "5826   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 11, 0, 0, 0, 0,...     10  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sample(n=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "X = np.array([x for x in df[\"byte_bfh\"]])\n",
    "y = np.array([y for y in df[\"class\"]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X shape:  (23356, 256)\n",
      "y shape:  (23356,)\n"
     ]
    }
   ],
   "source": [
    "print(\"X shape: \", X.shape)\n",
    "print(\"y shape: \", y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 70% train\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": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X training shape:  (16349, 256)\n",
      "X validation shape:  (3503, 256)\n",
      "X testing shape:  (3504, 256) \n",
      "\n",
      "y training shape:  (16349,)\n",
      "y validation shape:  (3503,)\n",
      "y testing shape:  (3504,)\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": 19,
   "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": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 19ms/step - accuracy: 0.5870 - loss: 1.7111 - val_accuracy: 0.7696 - val_loss: 0.7094\n",
      "Epoch 2/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 20ms/step - accuracy: 0.7870 - loss: 0.6578 - val_accuracy: 0.8067 - val_loss: 0.6672\n",
      "Epoch 3/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 19ms/step - accuracy: 0.8114 - loss: 0.5887 - val_accuracy: 0.8050 - val_loss: 0.6291\n",
      "Epoch 4/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 19ms/step - accuracy: 0.8204 - loss: 0.5357 - val_accuracy: 0.7799 - val_loss: 0.6367\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x11b7e97bf80>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "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": 21,
   "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": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m110/110\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 7ms/step\n"
     ]
    }
   ],
   "source": [
    "ffnn_pred = ffnn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feed Forward Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.7751141552511416.\n",
      "precision\t0.7929474873837826.\n",
      "recall\t\t0.7729189132917034.\n",
      "f1-score\t0.773417029689302.\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": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.95      0.98      0.97       278\n",
      "         pdf       0.97      0.80      0.88       306\n",
      "          ps       0.98      0.96      0.97       305\n",
      "         xls       0.98      0.94      0.96       301\n",
      "         ppt       0.42      0.46      0.44       309\n",
      "         swf       0.61      0.48      0.54       306\n",
      "         gif       0.87      0.92      0.89       294\n",
      "         jpg       0.75      0.81      0.78       310\n",
      "         png       0.46      0.58      0.51       203\n",
      "        html       0.60      0.96      0.74       287\n",
      "         txt       0.96      0.72      0.82       301\n",
      "         xml       0.96      0.66      0.78       304\n",
      "\n",
      "    accuracy                           0.78      3504\n",
      "   macro avg       0.79      0.77      0.77      3504\n",
      "weighted avg       0.80      0.78      0.78      3504\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ffnn_report = classification_report(y_test, ffnn_pred, target_names=CLASS_NAMES)\n",
    "print(ffnn_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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": 26,
   "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": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 17ms/step - accuracy: 0.6040 - loss: 1.2591 - val_accuracy: 0.7625 - val_loss: 0.7346\n",
      "Epoch 2/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 17ms/step - accuracy: 0.8006 - loss: 0.6320 - val_accuracy: 0.8022 - val_loss: 0.6328\n",
      "Epoch 3/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 16ms/step - accuracy: 0.8150 - loss: 0.5669 - val_accuracy: 0.7908 - val_loss: 0.6258\n",
      "Epoch 4/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m9s\u001b[0m 17ms/step - accuracy: 0.8137 - loss: 0.5469 - val_accuracy: 0.8059 - val_loss: 0.5728\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x11b7e979e80>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "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": 28,
   "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": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m110/110\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 8ms/step\n"
     ]
    }
   ],
   "source": [
    "ffnn2_pred = ffnn2.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feed Forward Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.8090753424657534.\n",
      "precision\t0.8143529681176749.\n",
      "recall\t\t0.8036643171800041.\n",
      "f1-score\t0.8029845414465298.\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": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.99      0.98      0.98       278\n",
      "         pdf       0.97      0.80      0.88       306\n",
      "          ps       1.00      0.94      0.97       305\n",
      "         xls       0.99      0.93      0.96       301\n",
      "         ppt       0.41      0.48      0.44       309\n",
      "         swf       0.68      0.41      0.51       306\n",
      "         gif       0.84      0.92      0.88       294\n",
      "         jpg       0.67      0.90      0.76       310\n",
      "         png       0.51      0.53      0.52       203\n",
      "        html       0.93      0.84      0.88       287\n",
      "         txt       0.89      0.97      0.93       301\n",
      "         xml       0.89      0.96      0.92       304\n",
      "\n",
      "    accuracy                           0.81      3504\n",
      "   macro avg       0.81      0.80      0.80      3504\n",
      "weighted avg       0.82      0.81      0.81      3504\n",
      "\n"
     ]
    }
   ],
   "source": [
    "ffnn2_report = classification_report(y_test, ffnn2_pred, target_names=CLASS_NAMES)\n",
    "print(ffnn2_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "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": 33,
   "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": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 8ms/step - accuracy: 0.5813 - loss: 2.3832 - val_accuracy: 0.7556 - val_loss: 0.7505\n",
      "Epoch 2/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 8ms/step - accuracy: 0.7887 - loss: 0.6339 - val_accuracy: 0.7936 - val_loss: 0.6317\n",
      "Epoch 3/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 8ms/step - accuracy: 0.8221 - loss: 0.5385 - val_accuracy: 0.7993 - val_loss: 0.6293\n",
      "Epoch 4/4\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 8ms/step - accuracy: 0.8341 - loss: 0.4819 - val_accuracy: 0.7822 - val_loss: 0.6615\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x11b28a66930>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "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": 35,
   "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": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m110/110\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step\n"
     ]
    }
   ],
   "source": [
    "cnn_pred = cnn.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Convolutional Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.781392694063927.\n",
      "precision\t0.8026784119161561.\n",
      "recall\t\t0.7711695204726531.\n",
      "f1-score\t0.7627243825878488.\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": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.95      0.99      0.97       278\n",
      "         pdf       0.94      0.80      0.87       306\n",
      "          ps       0.95      0.97      0.96       305\n",
      "         xls       0.97      0.91      0.94       301\n",
      "         ppt       0.66      0.23      0.34       309\n",
      "         swf       0.45      0.83      0.58       306\n",
      "         gif       0.69      0.95      0.80       294\n",
      "         jpg       0.75      0.75      0.75       310\n",
      "         png       0.68      0.30      0.41       203\n",
      "        html       0.74      0.90      0.81       287\n",
      "         txt       0.92      0.69      0.79       301\n",
      "         xml       0.92      0.95      0.93       304\n",
      "\n",
      "    accuracy                           0.78      3504\n",
      "   macro avg       0.80      0.77      0.76      3504\n",
      "weighted avg       0.81      0.78      0.77      3504\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cnn_report = classification_report(y_test, cnn_pred, target_names=CLASS_NAMES)\n",
    "print(cnn_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "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": 40,
   "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": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/6\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m21s\u001b[0m 39ms/step - accuracy: 0.5625 - loss: 2.7682 - val_accuracy: 0.7770 - val_loss: 0.7110\n",
      "Epoch 2/6\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m19s\u001b[0m 37ms/step - accuracy: 0.7707 - loss: 0.6695 - val_accuracy: 0.7942 - val_loss: 0.6164\n",
      "Epoch 3/6\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m19s\u001b[0m 37ms/step - accuracy: 0.8026 - loss: 0.5656 - val_accuracy: 0.7962 - val_loss: 0.6269\n",
      "Epoch 4/6\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m21s\u001b[0m 41ms/step - accuracy: 0.8308 - loss: 0.4909 - val_accuracy: 0.8321 - val_loss: 0.5244\n",
      "Epoch 5/6\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m22s\u001b[0m 42ms/step - accuracy: 0.8476 - loss: 0.4347 - val_accuracy: 0.8350 - val_loss: 0.5190\n",
      "Epoch 6/6\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m22s\u001b[0m 44ms/step - accuracy: 0.8616 - loss: 0.4044 - val_accuracy: 0.8427 - val_loss: 0.5541\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x11b2dbf14c0>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cnn2.fit(\n",
    "    X_train,\n",
    "    y_train,\n",
    "    validation_data=(X_val, y_val),\n",
    "    epochs=6,\n",
    "    batch_size=32\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m110/110\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 7ms/step\n"
     ]
    }
   ],
   "source": [
    "cnn2_pred = cnn2.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Convolutional Neural Network performance evaluation:\n",
      "\n",
      "accuracy\t0.838755707762557.\n",
      "precision\t0.8362490950715881.\n",
      "recall\t\t0.8340592495375126.\n",
      "f1-score\t0.8304974353496118.\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": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.97      0.97      0.97       278\n",
      "         pdf       0.96      0.82      0.89       306\n",
      "          ps       0.99      0.97      0.98       305\n",
      "         xls       0.98      0.96      0.97       301\n",
      "         ppt       0.67      0.43      0.52       309\n",
      "         swf       0.68      0.74      0.71       306\n",
      "         gif       0.83      0.93      0.88       294\n",
      "         jpg       0.69      0.88      0.77       310\n",
      "         png       0.57      0.59      0.58       203\n",
      "        html       0.85      0.90      0.87       287\n",
      "         txt       0.87      0.98      0.92       301\n",
      "         xml       0.97      0.85      0.90       304\n",
      "\n",
      "    accuracy                           0.84      3504\n",
      "   macro avg       0.84      0.83      0.83      3504\n",
      "weighted avg       0.84      0.84      0.84      3504\n",
      "\n"
     ]
    }
   ],
   "source": [
    "cnn2_report = classification_report(y_test, cnn2_pred, target_names=CLASS_NAMES)\n",
    "print(cnn2_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "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": 47,
   "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": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m57s\u001b[0m 106ms/step - accuracy: 0.3450 - loss: 1.7370 - val_accuracy: 0.5016 - val_loss: 1.2235\n",
      "Epoch 2/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m53s\u001b[0m 104ms/step - accuracy: 0.5332 - loss: 1.1840 - val_accuracy: 0.6158 - val_loss: 1.0351\n",
      "Epoch 3/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m67s\u001b[0m 131ms/step - accuracy: 0.6201 - loss: 1.0082 - val_accuracy: 0.6726 - val_loss: 0.8957\n",
      "Epoch 4/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m56s\u001b[0m 109ms/step - accuracy: 0.6751 - loss: 0.8696 - val_accuracy: 0.6814 - val_loss: 0.8381\n",
      "Epoch 5/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m57s\u001b[0m 112ms/step - accuracy: 0.7074 - loss: 0.7968 - val_accuracy: 0.7351 - val_loss: 0.7421\n",
      "Epoch 6/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m67s\u001b[0m 130ms/step - accuracy: 0.7402 - loss: 0.7289 - val_accuracy: 0.7454 - val_loss: 0.7420\n",
      "Epoch 7/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m55s\u001b[0m 109ms/step - accuracy: 0.7529 - loss: 0.7044 - val_accuracy: 0.7508 - val_loss: 0.7004\n",
      "Epoch 8/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m60s\u001b[0m 117ms/step - accuracy: 0.7642 - loss: 0.6591 - val_accuracy: 0.7439 - val_loss: 0.7222\n",
      "Epoch 9/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m69s\u001b[0m 134ms/step - accuracy: 0.7566 - loss: 0.7014 - val_accuracy: 0.7599 - val_loss: 0.7075\n",
      "Epoch 10/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m53s\u001b[0m 103ms/step - accuracy: 0.7795 - loss: 0.6414 - val_accuracy: 0.7768 - val_loss: 0.6406\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x11b732fd8b0>"
      ]
     },
     "execution_count": 48,
     "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": 49,
   "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": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m110/110\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 30ms/step\n"
     ]
    }
   ],
   "source": [
    "gru_pred = gru.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Gated Reccurent Unit performance evaluation:\n",
      "\n",
      "accuracy\t0.7699771689497716.\n",
      "precision\t0.7707218791858405.\n",
      "recall\t\t0.7648734586800229.\n",
      "f1-score\t0.7616587516462746.\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": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.87      0.96      0.91       278\n",
      "         pdf       0.93      0.74      0.83       306\n",
      "          ps       0.94      0.94      0.94       305\n",
      "         xls       0.93      0.89      0.91       301\n",
      "         ppt       0.47      0.37      0.41       309\n",
      "         swf       0.69      0.67      0.68       306\n",
      "         gif       0.90      0.98      0.94       294\n",
      "         jpg       0.61      0.83      0.71       310\n",
      "         png       0.52      0.48      0.50       203\n",
      "        html       0.64      0.88      0.74       287\n",
      "         txt       0.87      0.72      0.79       301\n",
      "         xml       0.88      0.72      0.79       304\n",
      "\n",
      "    accuracy                           0.77      3504\n",
      "   macro avg       0.77      0.76      0.76      3504\n",
      "weighted avg       0.78      0.77      0.77      3504\n",
      "\n"
     ]
    }
   ],
   "source": [
    "gru_report = classification_report(y_test, gru_pred, target_names=CLASS_NAMES)\n",
    "print(gru_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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": 54,
   "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": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m55s\u001b[0m 102ms/step - accuracy: 0.3459 - loss: 1.7231 - val_accuracy: 0.5481 - val_loss: 1.2495\n",
      "Epoch 2/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m54s\u001b[0m 105ms/step - accuracy: 0.5609 - loss: 1.1945 - val_accuracy: 0.6203 - val_loss: 1.0592\n",
      "Epoch 3/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m45s\u001b[0m 89ms/step - accuracy: 0.6519 - loss: 0.9868 - val_accuracy: 0.6697 - val_loss: 0.9335\n",
      "Epoch 4/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m50s\u001b[0m 97ms/step - accuracy: 0.6982 - loss: 0.8530 - val_accuracy: 0.7077 - val_loss: 0.8338\n",
      "Epoch 5/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m52s\u001b[0m 102ms/step - accuracy: 0.7142 - loss: 0.8042 - val_accuracy: 0.7462 - val_loss: 0.7552\n",
      "Epoch 6/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m46s\u001b[0m 90ms/step - accuracy: 0.7290 - loss: 0.7617 - val_accuracy: 0.7345 - val_loss: 0.7518\n",
      "Epoch 7/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m40s\u001b[0m 79ms/step - accuracy: 0.7496 - loss: 0.7029 - val_accuracy: 0.7436 - val_loss: 0.7129\n",
      "Epoch 8/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m56s\u001b[0m 110ms/step - accuracy: 0.7571 - loss: 0.6712 - val_accuracy: 0.7631 - val_loss: 0.6843\n",
      "Epoch 9/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m55s\u001b[0m 107ms/step - accuracy: 0.7617 - loss: 0.6658 - val_accuracy: 0.7631 - val_loss: 0.6614\n",
      "Epoch 10/10\n",
      "\u001b[1m511/511\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m42s\u001b[0m 82ms/step - accuracy: 0.7690 - loss: 0.6422 - val_accuracy: 0.7613 - val_loss: 0.6774\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.history.History at 0x11b28eeaff0>"
      ]
     },
     "execution_count": 55,
     "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": 56,
   "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": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[1m110/110\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3s\u001b[0m 28ms/step\n"
     ]
    }
   ],
   "source": [
    "lstm_pred = lstm.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Long Short-Term Memory performance evaluation:\n",
      "\n",
      "accuracy\t0.7648401826484018.\n",
      "precision\t0.7596491797075121.\n",
      "recall\t\t0.759291283091912.\n",
      "f1-score\t0.7563438755892499.\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": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "         doc       0.87      0.88      0.88       278\n",
      "         pdf       0.86      0.77      0.81       306\n",
      "          ps       0.95      0.92      0.93       305\n",
      "         xls       0.89      0.88      0.88       301\n",
      "         ppt       0.45      0.33      0.38       309\n",
      "         swf       0.66      0.59      0.62       306\n",
      "         gif       0.91      0.95      0.93       294\n",
      "         jpg       0.58      0.81      0.67       310\n",
      "         png       0.43      0.48      0.45       203\n",
      "        html       0.84      0.81      0.83       287\n",
      "         txt       0.82      0.85      0.84       301\n",
      "         xml       0.85      0.85      0.85       304\n",
      "\n",
      "    accuracy                           0.76      3504\n",
      "   macro avg       0.76      0.76      0.76      3504\n",
      "weighted avg       0.77      0.76      0.76      3504\n",
      "\n"
     ]
    }
   ],
   "source": [
    "lstm_report = classification_report(y_test, lstm_pred, target_names=CLASS_NAMES)\n",
    "print(lstm_report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "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
}