IoTID20_Classification.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "IoTID20 Classification.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNOx1iSWk/XhD+vGaGEUUDF",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/osamazafar980/IoTID20-Data-Binary-Classification/blob/master/IoTID20_Classification.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9XIn0pc-REs7",
        "colab_type": "text"
      },
      "source": [
        "**IMPORTING LIBRARIES**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pVe4jyzLOB58",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import tensorflow as tf\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Dense, BatchNormalization\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mj6zuRtzRRee",
        "colab_type": "text"
      },
      "source": [
        "**MOUNTING DRIVE AND LOADING DATA SET**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I9HLqYquOYiZ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 120
        },
        "outputId": "7d6ea59d-14a6-4595-e8b6-6ff906b7f10a"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YEMlRPAVRwH5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 759
        },
        "outputId": "72c9cca0-4e66-4352-ca23-67daf75f8f1b"
      },
      "source": [
        "data =pd.read_csv('/content/drive/My Drive/Datasets/IoTID20.csv')\n",
        "data"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>Flow_ID</th>\n",
              "      <th>Src_IP</th>\n",
              "      <th>Src_Port</th>\n",
              "      <th>Dst_IP</th>\n",
              "      <th>Dst_Port</th>\n",
              "      <th>Protocol</th>\n",
              "      <th>Timestamp</th>\n",
              "      <th>Flow_Duration</th>\n",
              "      <th>Tot_Fwd_Pkts</th>\n",
              "      <th>Tot_Bwd_Pkts</th>\n",
              "      <th>TotLen_Fwd_Pkts</th>\n",
              "      <th>TotLen_Bwd_Pkts</th>\n",
              "      <th>Fwd_Pkt_Len_Max</th>\n",
              "      <th>Fwd_Pkt_Len_Min</th>\n",
              "      <th>Fwd_Pkt_Len_Mean</th>\n",
              "      <th>Fwd_Pkt_Len_Std</th>\n",
              "      <th>Bwd_Pkt_Len_Max</th>\n",
              "      <th>Bwd_Pkt_Len_Min</th>\n",
              "      <th>Bwd_Pkt_Len_Mean</th>\n",
              "      <th>Bwd_Pkt_Len_Std</th>\n",
              "      <th>Flow_Byts/s</th>\n",
              "      <th>Flow_Pkts/s</th>\n",
              "      <th>Flow_IAT_Mean</th>\n",
              "      <th>Flow_IAT_Std</th>\n",
              "      <th>Flow_IAT_Max</th>\n",
              "      <th>Flow_IAT_Min</th>\n",
              "      <th>Fwd_IAT_Tot</th>\n",
              "      <th>Fwd_IAT_Mean</th>\n",
              "      <th>Bwd_IAT_Mean</th>\n",
              "      <th>Fwd_IAT_Max</th>\n",
              "      <th>Fwd_IAT_Min</th>\n",
              "      <th>Bwd_IAT_Tot</th>\n",
              "      <th>Bwd_IAT_Mean.1</th>\n",
              "      <th>Bwd_IAT_Std</th>\n",
              "      <th>Bwd_IAT_Max</th>\n",
              "      <th>Bwd_IAT_Min</th>\n",
              "      <th>Fwd_PSH_Flags</th>\n",
              "      <th>Bwd_PSH_Flags</th>\n",
              "      <th>Fwd_URG_Flags</th>\n",
              "      <th>Bwd_URG_Flags</th>\n",
              "      <th>...</th>\n",
              "      <th>Pkt_Len_Mean</th>\n",
              "      <th>Pkt_Len_Std</th>\n",
              "      <th>Pkt_Len_Var</th>\n",
              "      <th>FIN_Flag_Cnt</th>\n",
              "      <th>SYN_Flag_Cnt</th>\n",
              "      <th>RST_Flag_Cnt</th>\n",
              "      <th>PSH_Flag_Cnt</th>\n",
              "      <th>ACK_Flag_Cnt</th>\n",
              "      <th>URG_Flag_Cnt</th>\n",
              "      <th>CWE_Flag_Count</th>\n",
              "      <th>ECE_Flag_Cnt</th>\n",
              "      <th>Down/Up_Ratio</th>\n",
              "      <th>Pkt_Size_Avg</th>\n",
              "      <th>Fwd_Seg_Size_Avg</th>\n",
              "      <th>Bwd_Seg_Size_Avg</th>\n",
              "      <th>Fwd_Byts/b_Avg</th>\n",
              "      <th>Fwd_Pkts/b_Avg</th>\n",
              "      <th>Fwd_Blk_Rate_Avg</th>\n",
              "      <th>Bwd_Byts/b_Avg</th>\n",
              "      <th>Bwd_Pkts/b_Avg</th>\n",
              "      <th>Bwd_Blk_Rate_Avg</th>\n",
              "      <th>Subflow_Fwd_Pkts</th>\n",
              "      <th>Subflow_Fwd_Byts</th>\n",
              "      <th>Subflow_Bwd_Pkts</th>\n",
              "      <th>Subflow_Bwd_Byts</th>\n",
              "      <th>Init_Fwd_Win_Byts</th>\n",
              "      <th>Init_Bwd_Win_Byts</th>\n",
              "      <th>Fwd_Act_Data_Pkts</th>\n",
              "      <th>Fwd_Seg_Size_Min</th>\n",
              "      <th>Active_Mean</th>\n",
              "      <th>Active_Std</th>\n",
              "      <th>Active_Max</th>\n",
              "      <th>Active_Min</th>\n",
              "      <th>Idle_Mean</th>\n",
              "      <th>Idle_Std</th>\n",
              "      <th>Idle_Max</th>\n",
              "      <th>Idle_Min</th>\n",
              "      <th>Label</th>\n",
              "      <th>Cat</th>\n",
              "      <th>Sub_Cat</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>192.168.0.13-192.168.0.16-10000-10101-17</td>\n",
              "      <td>192.168.0.13</td>\n",
              "      <td>10000</td>\n",
              "      <td>192.168.0.16</td>\n",
              "      <td>10101</td>\n",
              "      <td>17</td>\n",
              "      <td>25/07/2019 03:25:53 AM</td>\n",
              "      <td>75</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>982.0</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>982.0</td>\n",
              "      <td>982.0</td>\n",
              "      <td>982.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>1430.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>3.216000e+07</td>\n",
              "      <td>26666.666667</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1280.666667</td>\n",
              "      <td>258.652921</td>\n",
              "      <td>66901.333333</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1921.000000</td>\n",
              "      <td>982.0</td>\n",
              "      <td>1430.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>982</td>\n",
              "      <td>1</td>\n",
              "      <td>1430</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>75.0</td>\n",
              "      <td>75.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>Mirai</td>\n",
              "      <td>Mirai-Ackflooding</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>192.168.0.13-222.160.179.132-554-2179-6</td>\n",
              "      <td>222.160.179.132</td>\n",
              "      <td>2179</td>\n",
              "      <td>192.168.0.13</td>\n",
              "      <td>554</td>\n",
              "      <td>6</td>\n",
              "      <td>26/05/2019 10:11:06 PM</td>\n",
              "      <td>5310</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>564.971751</td>\n",
              "      <td>2655.0</td>\n",
              "      <td>2261.327486</td>\n",
              "      <td>4254.0</td>\n",
              "      <td>1056.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>5310.0</td>\n",
              "      <td>5310.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>5310.0</td>\n",
              "      <td>5310.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>-1</td>\n",
              "      <td>14600</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2655.0</td>\n",
              "      <td>2261.327486</td>\n",
              "      <td>4254.0</td>\n",
              "      <td>1056.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>DoS</td>\n",
              "      <td>DoS-Synflooding</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>192.168.0.13-192.168.0.16-9020-52727-6</td>\n",
              "      <td>192.168.0.16</td>\n",
              "      <td>52727</td>\n",
              "      <td>192.168.0.13</td>\n",
              "      <td>9020</td>\n",
              "      <td>6</td>\n",
              "      <td>11/07/2019 01:24:48 AM</td>\n",
              "      <td>141</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2806.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>935.333333</td>\n",
              "      <td>784.041666</td>\n",
              "      <td>1.990071e+07</td>\n",
              "      <td>21276.595745</td>\n",
              "      <td>70.5</td>\n",
              "      <td>0.707107</td>\n",
              "      <td>71.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>141.0</td>\n",
              "      <td>70.5</td>\n",
              "      <td>0.707107</td>\n",
              "      <td>71.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1048.500000</td>\n",
              "      <td>679.000000</td>\n",
              "      <td>461041.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1398.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>935.333333</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2806</td>\n",
              "      <td>-1</td>\n",
              "      <td>1869</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>70.5</td>\n",
              "      <td>0.707107</td>\n",
              "      <td>71.0</td>\n",
              "      <td>70.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>Scan</td>\n",
              "      <td>Scan Port OS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>192.168.0.13-192.168.0.16-9020-52964-6</td>\n",
              "      <td>192.168.0.16</td>\n",
              "      <td>52964</td>\n",
              "      <td>192.168.0.13</td>\n",
              "      <td>9020</td>\n",
              "      <td>6</td>\n",
              "      <td>04/09/2019 03:58:17 AM</td>\n",
              "      <td>151</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2776.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>1388.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.838411e+07</td>\n",
              "      <td>13245.033113</td>\n",
              "      <td>151.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>151.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>151.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1388.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2082.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1388.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2776</td>\n",
              "      <td>-1</td>\n",
              "      <td>1869</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>151.0</td>\n",
              "      <td>151.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>Mirai</td>\n",
              "      <td>Mirai-Hostbruteforceg</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>192.168.0.1-239.255.255.250-36763-1900-17</td>\n",
              "      <td>192.168.0.1</td>\n",
              "      <td>36763</td>\n",
              "      <td>239.255.255.250</td>\n",
              "      <td>1900</td>\n",
              "      <td>17</td>\n",
              "      <td>10/09/2019 01:41:18 AM</td>\n",
              "      <td>153</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>886.0</td>\n",
              "      <td>420.0</td>\n",
              "      <td>452.0</td>\n",
              "      <td>434.0</td>\n",
              "      <td>443.0</td>\n",
              "      <td>12.727922</td>\n",
              "      <td>420.0</td>\n",
              "      <td>420.0</td>\n",
              "      <td>420.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>8.535948e+06</td>\n",
              "      <td>19607.843137</td>\n",
              "      <td>76.5</td>\n",
              "      <td>0.707107</td>\n",
              "      <td>77.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>431.500000</td>\n",
              "      <td>15.176737</td>\n",
              "      <td>230.333333</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>575.333333</td>\n",
              "      <td>443.0</td>\n",
              "      <td>420.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>886</td>\n",
              "      <td>1</td>\n",
              "      <td>420</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>76.5</td>\n",
              "      <td>0.707107</td>\n",
              "      <td>77.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>Mirai</td>\n",
              "      <td>Mirai-Hostbruteforceg</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625778</th>\n",
              "      <td>192.168.0.24-210.89.164.90-56112-8043-17</td>\n",
              "      <td>192.168.0.24</td>\n",
              "      <td>56112</td>\n",
              "      <td>210.89.164.90</td>\n",
              "      <td>8043</td>\n",
              "      <td>17</td>\n",
              "      <td>25/07/2019 03:25:00 AM</td>\n",
              "      <td>277</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>18.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>18.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.299639e+05</td>\n",
              "      <td>7220.216606</td>\n",
              "      <td>277.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>277.0</td>\n",
              "      <td>277.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>27.000000</td>\n",
              "      <td>18.0</td>\n",
              "      <td>18.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>18</td>\n",
              "      <td>1</td>\n",
              "      <td>18</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>277.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>277.0</td>\n",
              "      <td>277.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>Mirai</td>\n",
              "      <td>Mirai-UDP Flooding</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625779</th>\n",
              "      <td>192.168.0.13-222.131.171.244-554-4570-6</td>\n",
              "      <td>222.131.171.244</td>\n",
              "      <td>4570</td>\n",
              "      <td>192.168.0.13</td>\n",
              "      <td>554</td>\n",
              "      <td>6</td>\n",
              "      <td>26/05/2019 10:06:51 PM</td>\n",
              "      <td>1658</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>1206.272618</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>-1</td>\n",
              "      <td>14600</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>1658.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>DoS</td>\n",
              "      <td>DoS-Synflooding</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625780</th>\n",
              "      <td>192.168.0.13-192.168.0.16-9020-52739-6</td>\n",
              "      <td>192.168.0.16</td>\n",
              "      <td>52739</td>\n",
              "      <td>192.168.0.13</td>\n",
              "      <td>9020</td>\n",
              "      <td>6</td>\n",
              "      <td>11/07/2019 01:29:09 AM</td>\n",
              "      <td>77</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000e+00</td>\n",
              "      <td>25974.025974</td>\n",
              "      <td>77.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>77.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>-1</td>\n",
              "      <td>32679</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>77.0</td>\n",
              "      <td>77.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>Scan</td>\n",
              "      <td>Scan Port OS</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625781</th>\n",
              "      <td>192.168.0.13-192.168.0.16-9020-49784-6</td>\n",
              "      <td>192.168.0.13</td>\n",
              "      <td>9020</td>\n",
              "      <td>192.168.0.16</td>\n",
              "      <td>49784</td>\n",
              "      <td>6</td>\n",
              "      <td>20/05/2019 05:00:29 AM</td>\n",
              "      <td>240</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2776.0</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>1388.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1.735000e+07</td>\n",
              "      <td>12500.000000</td>\n",
              "      <td>120.0</td>\n",
              "      <td>7.071068</td>\n",
              "      <td>125.0</td>\n",
              "      <td>115.0</td>\n",
              "      <td>125.0</td>\n",
              "      <td>125.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>125.0</td>\n",
              "      <td>125.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1388.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1850.666667</td>\n",
              "      <td>1388.0</td>\n",
              "      <td>1388.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2776</td>\n",
              "      <td>1</td>\n",
              "      <td>1388</td>\n",
              "      <td>-1</td>\n",
              "      <td>1869</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>120.0</td>\n",
              "      <td>7.071068</td>\n",
              "      <td>125.0</td>\n",
              "      <td>115.0</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Normal</td>\n",
              "      <td>Normal</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>625782</th>\n",
              "      <td>192.168.0.13-192.168.0.16-10000-10101-17</td>\n",
              "      <td>192.168.0.13</td>\n",
              "      <td>10000</td>\n",
              "      <td>192.168.0.16</td>\n",
              "      <td>10101</td>\n",
              "      <td>17</td>\n",
              "      <td>25/07/2019 03:25:10 AM</td>\n",
              "      <td>198</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2860.0</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>1430.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.166667e+07</td>\n",
              "      <td>15151.515152</td>\n",
              "      <td>99.0</td>\n",
              "      <td>32.526912</td>\n",
              "      <td>122.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>122.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>1430.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1906.666667</td>\n",
              "      <td>1430.0</td>\n",
              "      <td>1430.000000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>2860</td>\n",
              "      <td>1</td>\n",
              "      <td>1430</td>\n",
              "      <td>-1</td>\n",
              "      <td>-1</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>99.0</td>\n",
              "      <td>32.526912</td>\n",
              "      <td>122.0</td>\n",
              "      <td>76.0</td>\n",
              "      <td>Anomaly</td>\n",
              "      <td>Mirai</td>\n",
              "      <td>Mirai-UDP Flooding</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>625783 rows × 86 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                          Flow_ID  ...                Sub_Cat\n",
              "0        192.168.0.13-192.168.0.16-10000-10101-17  ...      Mirai-Ackflooding\n",
              "1         192.168.0.13-222.160.179.132-554-2179-6  ...        DoS-Synflooding\n",
              "2          192.168.0.13-192.168.0.16-9020-52727-6  ...           Scan Port OS\n",
              "3          192.168.0.13-192.168.0.16-9020-52964-6  ...  Mirai-Hostbruteforceg\n",
              "4       192.168.0.1-239.255.255.250-36763-1900-17  ...  Mirai-Hostbruteforceg\n",
              "...                                           ...  ...                    ...\n",
              "625778   192.168.0.24-210.89.164.90-56112-8043-17  ...     Mirai-UDP Flooding\n",
              "625779    192.168.0.13-222.131.171.244-554-4570-6  ...        DoS-Synflooding\n",
              "625780     192.168.0.13-192.168.0.16-9020-52739-6  ...           Scan Port OS\n",
              "625781     192.168.0.13-192.168.0.16-9020-49784-6  ...                 Normal\n",
              "625782   192.168.0.13-192.168.0.16-10000-10101-17  ...     Mirai-UDP Flooding\n",
              "\n",
              "[625783 rows x 86 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_9HzEhdCXz73",
        "colab_type": "text"
      },
      "source": [
        "**PREPROCESSING AND CLEANING DATA**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I6rAO_BERW4T",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def clean_dataset(df):\n",
        "    assert isinstance(df, pd.DataFrame), \"df needs to be a pd.DataFrame\"\n",
        "    df.dropna(inplace=True)\n",
        "    indices_to_keep = ~df.isin([np.nan, np.inf, -np.inf]).any(1)\n",
        "    return df[indices_to_keep]\n",
        "data=clean_dataset(data)\n",
        "data = data.to_numpy()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "I3l2TKVIU5HD",
        "colab_type": "text"
      },
      "source": [
        "**LABEL ENCODING**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CfbcGPnsU-mH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "np.random.shuffle(data) \n",
        "X=data[:,7:83]\n",
        "Y=data[:,83]\n",
        "Y[Y=='Anomaly']=0\n",
        "Y[Y=='Normal']=1\n",
        "minMax= MinMaxScaler()\n",
        "X = minMax.fit_transform(X)\n",
        "std = StandardScaler()\n",
        "X = std.fit_transform(X)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CQ65WNAiToaL",
        "colab_type": "text"
      },
      "source": [
        "**SPLITING DATA**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ueIHC9irSKtG",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.33, random_state=1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P9MXSdLifseX",
        "colab_type": "text"
      },
      "source": [
        "**MODEL**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n_SRNuxnUOya",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 284
        },
        "outputId": "af93c35b-fabd-403d-eda6-5ad6589577cf"
      },
      "source": [
        "model = Sequential(\n",
        "    [\n",
        "     Dense(32,activation='relu',input_shape=X_train.shape, kernel_initializer='random_normal'),\n",
        "     Dense(32,activation='relu', kernel_initializer='random_normal'),\n",
        "     Dense(32,activation='relu', kernel_initializer='random_normal'),\n",
        "     Dense(1,activation='sigmoid', kernel_initializer='random_normal'),\n",
        "    ]\n",
        ")\n",
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense (Dense)                (None, 419028, 32)        2464      \n",
            "_________________________________________________________________\n",
            "dense_1 (Dense)              (None, 419028, 32)        1056      \n",
            "_________________________________________________________________\n",
            "dense_2 (Dense)              (None, 419028, 32)        1056      \n",
            "_________________________________________________________________\n",
            "dense_3 (Dense)              (None, 419028, 1)         33        \n",
            "=================================================================\n",
            "Total params: 4,609\n",
            "Trainable params: 4,609\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-bmn9vXJgpGB",
        "colab_type": "text"
      },
      "source": [
        "**COMPILING AND TRAINING MODEL**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w3Lac_i_ginb",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "outputId": "a7f2e9e3-3b94-4624-ba20-eb26ea824d7c"
      },
      "source": [
        "model.compile(\n",
        "    optimizer='adam',\n",
        "    loss='binary_crossentropy',\n",
        "    metrics=['accuracy']\n",
        ")\n",
        "X_train = tf.convert_to_tensor(X_train,np.float32)\n",
        "y_train = tf.convert_to_tensor(y_train,np.float32)\n",
        "print(X_train.shape)\n",
        "print(y_train.shape)\n",
        "history=model.fit(X_train, y_train,epochs=10, batch_size=50)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(419028, 76)\n",
            "(419028,)\n",
            "Epoch 1/10\n",
            "WARNING:tensorflow:Model was constructed with shape (None, 419028, 76) for input Tensor(\"dense_input:0\", shape=(None, 419028, 76), dtype=float32), but it was called on an input with incompatible shape (None, 76).\n",
            "WARNING:tensorflow:Model was constructed with shape (None, 419028, 76) for input Tensor(\"dense_input:0\", shape=(None, 419028, 76), dtype=float32), but it was called on an input with incompatible shape (None, 76).\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0388 - accuracy: 0.9881\n",
            "Epoch 2/10\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0384 - accuracy: 0.9882\n",
            "Epoch 3/10\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0381 - accuracy: 0.9882\n",
            "Epoch 4/10\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0381 - accuracy: 0.9883\n",
            "Epoch 5/10\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0378 - accuracy: 0.9882\n",
            "Epoch 6/10\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0377 - accuracy: 0.9884\n",
            "Epoch 7/10\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0375 - accuracy: 0.9884\n",
            "Epoch 8/10\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0375 - accuracy: 0.9884\n",
            "Epoch 9/10\n",
            "8381/8381 [==============================] - 12s 1ms/step - loss: 0.0371 - accuracy: 0.9885\n",
            "Epoch 10/10\n",
            "8381/8381 [==============================] - 13s 2ms/step - loss: 0.0370 - accuracy: 0.9885\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UkleByDdWzcZ",
        "colab_type": "text"
      },
      "source": [
        "**EVALUTATING MODEL**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KzG0_xH8hYUJ",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 104
        },
        "outputId": "d20aafa7-2a97-489e-b657-8ed656954f7e"
      },
      "source": [
        "loss,accuracy = model.evaluate(tf.convert_to_tensor(X_test,np.float32),tf.convert_to_tensor(y_test,np.float32))\n",
        "print(\"Loss: \", loss)\n",
        "print('Accuracy: ',accuracy*100)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Model was constructed with shape (None, 419028, 76) for input Tensor(\"dense_input:0\", shape=(None, 419028, 76), dtype=float32), but it was called on an input with incompatible shape (None, 76).\n",
            "6450/6450 [==============================] - 7s 1ms/step - loss: 0.0389 - accuracy: 0.9883\n",
            "Loss:  0.038903459906578064\n",
            "Accuracy:  98.83131980895996\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0M-Mu2DX555V",
        "colab_type": "text"
      },
      "source": [
        "**Visualizing Evaluation**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V9nIGsQGXhqG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "outputId": "8960ac28-c1d1-482d-f6e7-546f4b59cbed"
      },
      "source": [
        "# summarize history for accuracy\n",
        "plt.plot(history.history['accuracy'])\n",
        "plt.title('model accuracy')\n",
        "plt.ylabel('accuracy')\n",
        "plt.xlabel('epoch')\n",
        "plt.show()\n",
        "# summarize history for loss\n",
        "plt.plot(history.history['loss'])\n",
        "plt.title('model loss')\n",
        "plt.ylabel('loss')\n",
        "plt.xlabel('epoch')\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LV8dJMNQ7h5A",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}