Tanuj_simple_feed_loan.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xfZrWaq-J96P"
   },
   "source": [
    "\n",
    "# Load the dataset with all libraries\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "-9zd3GBCJ96Q",
    "outputId": "ee445ca1-f51f-400e-ca01-acf3aad4d638"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "from google.colab import drive\n",
    "drive.mount('/content/drive')\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Dropout\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras import regularizers\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.svm import SVC\n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.preprocessing import OneHotEncoder\n",
    "from sklearn.preprocessing import MinMaxScaler\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score\n",
    "import pandas as pd\n",
    "from sklearn.metrics import roc_curve, auc\n",
    "\n",
    "\n",
    "df = pd.read_excel('/content/loan.xlsx')\n",
    "\n",
    "df.replace('accept', 1, inplace=True)\n",
    "df.replace('reject', 0, inplace=True)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "wmkm3Q0MLP2q",
    "outputId": "b56d1804-1388-47ee-a596-b4385413bdf6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    237\n",
      "1    192\n",
      "Name: Decision, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "x = df['Decision'].value_counts().head(10)\n",
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "BKhMplRlJ96R",
    "outputId": "49080153-95e5-499c-ea8e-f9ff8bb7f968"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Sex', 'Age', 'Time_at_address', 'Res_status', 'Telephone',\n",
      "       'Occupation', 'Job_status', 'Time_employed', 'Time_bank', 'Liab_ref',\n",
      "       'Acc_ref', 'Home_Expn', 'Balance', 'Decision'],\n",
      "      dtype='object')\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Sex                0\n",
       "Age                0\n",
       "Time_at_address    0\n",
       "Res_status         0\n",
       "Telephone          0\n",
       "Occupation         0\n",
       "Job_status         0\n",
       "Time_employed      0\n",
       "Time_bank          0\n",
       "Liab_ref           0\n",
       "Acc_ref            0\n",
       "Home_Expn          0\n",
       "Balance            0\n",
       "Decision           0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(df.columns)\n",
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "jw90yOTOJ96R",
    "outputId": "b5a03f22-a70b-4abb-e2dd-847fdda0c8bf"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Age  Time_at_address  Time_employed  Time_bank  Home_Expn  Balance  \\\n",
      "0  50.750000            0.585              0          0        145        0   \n",
      "1  19.670000           10.000              0          0        140        0   \n",
      "2  52.830002           15.000              5         14          0     2200   \n",
      "3  22.670000            2.540              2          0          0        0   \n",
      "4  29.250000           13.000              0          0        228        0   \n",
      "\n",
      "   Decision  Sex_F  Sex_M  Res_status_owner  ...  Job_status_military  \\\n",
      "0         0    0.0    1.0               1.0  ...                  0.0   \n",
      "1         0    0.0    1.0               0.0  ...                  0.0   \n",
      "2         1    1.0    0.0               1.0  ...                  0.0   \n",
      "3         1    0.0    1.0               0.0  ...                  0.0   \n",
      "4         0    0.0    1.0               1.0  ...                  0.0   \n",
      "\n",
      "   Job_status_private_s  Job_status_retired  Job_status_self_empl  \\\n",
      "0                   0.0                 0.0                   0.0   \n",
      "1                   0.0                 0.0                   0.0   \n",
      "2                   1.0                 0.0                   0.0   \n",
      "3                   0.0                 0.0                   0.0   \n",
      "4                   0.0                 0.0                   0.0   \n",
      "\n",
      "   Job_status_student  Job_status_unemploye  Liab_ref_f  Liab_ref_t  \\\n",
      "0                 0.0                   1.0         1.0         0.0   \n",
      "1                 0.0                   0.0         0.0         1.0   \n",
      "2                 0.0                   0.0         1.0         0.0   \n",
      "3                 0.0                   0.0         1.0         0.0   \n",
      "4                 0.0                   0.0         1.0         0.0   \n",
      "\n",
      "   Acc_ref_given  Acc_ref_oth_inst_  \n",
      "0            1.0                0.0  \n",
      "1            1.0                0.0  \n",
      "2            1.0                0.0  \n",
      "3            1.0                0.0  \n",
      "4            1.0                0.0  \n",
      "\n",
      "[5 rows x 36 columns]\n"
     ]
    }
   ],
   "source": [
    "cat_cols = ['Sex', 'Res_status', 'Telephone', 'Occupation', 'Job_status','Liab_ref','Acc_ref']\n",
    "\n",
    "encoder = OneHotEncoder()\n",
    "encoded_cols = encoder.fit_transform(df[cat_cols])\n",
    "encoded_df = pd.DataFrame(encoded_cols.toarray(), columns=encoder.get_feature_names_out(cat_cols))\n",
    "df = pd.concat([df.drop(cat_cols, axis=1), encoded_df], axis=1)\n",
    "print(df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "rtRXdEtQJ96S",
    "outputId": "ea44e527-694f-46f7-b87e-7ecbd59b939c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Age                     float64\n",
      "Time_at_address         float64\n",
      "Time_employed             int64\n",
      "Time_bank                 int64\n",
      "Home_Expn                 int64\n",
      "Balance                   int64\n",
      "Decision                  int64\n",
      "Sex_F                   float64\n",
      "Sex_M                   float64\n",
      "Res_status_owner        float64\n",
      "Res_status_rent         float64\n",
      "Telephone_given         float64\n",
      "Telephone_not_given     float64\n",
      "Occupation_creative_    float64\n",
      "Occupation_driver       float64\n",
      "Occupation_executive    float64\n",
      "Occupation_guard_etc    float64\n",
      "Occupation_labourer     float64\n",
      "Occupation_manager      float64\n",
      "Occupation_office_st    float64\n",
      "Occupation_productio    float64\n",
      "Occupation_professio    float64\n",
      "Occupation_sales        float64\n",
      "Occupation_semi_pro     float64\n",
      "Occupation_unemploye    float64\n",
      "Job_status_governmen    float64\n",
      "Job_status_military     float64\n",
      "Job_status_private_s    float64\n",
      "Job_status_retired      float64\n",
      "Job_status_self_empl    float64\n",
      "Job_status_student      float64\n",
      "Job_status_unemploye    float64\n",
      "Liab_ref_f              float64\n",
      "Liab_ref_t              float64\n",
      "Acc_ref_given           float64\n",
      "Acc_ref_oth_inst_       float64\n",
      "dtype: object\n"
     ]
    }
   ],
   "source": [
    "print(df.dtypes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "meFFJyAlJ96S"
   },
   "source": [
    "2.Found out corelation matrix to determine relevant columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "08RfWNjAJ96S",
    "outputId": "0e9c5edb-3f76-4bb3-e49f-27e126613463"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Decision                1.000000\n",
      "Time_bank               0.455942\n",
      "Time_employed           0.339833\n",
      "Balance                 0.191858\n",
      "Age                     0.181241\n",
      "Occupation_professio    0.165153\n",
      "Time_at_address         0.163298\n",
      "Job_status_governmen    0.158575\n",
      "Telephone_given         0.139104\n",
      "Res_status_owner        0.139104\n",
      "Occupation_semi_pro     0.134504\n",
      "Occupation_office_st    0.133674\n",
      "Acc_ref_given           0.106354\n",
      "Job_status_retired      0.083847\n",
      "Liab_ref_t              0.068508\n",
      "Occupation_executive    0.067796\n",
      "Sex_F                   0.052564\n",
      "Occupation_creative_    0.032268\n",
      "Occupation_productio    0.028458\n",
      "Job_status_self_empl   -0.009342\n",
      "Job_status_student     -0.010385\n",
      "Occupation_manager     -0.029066\n",
      "Occupation_sales       -0.033932\n",
      "Job_status_military    -0.043507\n",
      "Job_status_private_s   -0.044389\n",
      "Sex_M                  -0.052564\n",
      "Liab_ref_f             -0.068508\n",
      "Occupation_driver      -0.078199\n",
      "Home_Expn              -0.087311\n",
      "Acc_ref_oth_inst_      -0.106354\n",
      "Occupation_labourer    -0.107222\n",
      "Occupation_guard_etc   -0.131258\n",
      "Telephone_not_given    -0.139104\n",
      "Res_status_rent        -0.139104\n",
      "Occupation_unemploye   -0.173276\n",
      "Job_status_unemploye   -0.178776\n",
      "Name: Decision, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "corr_matrix = df.corr()['Decision']\n",
    "sorted_corr = corr_matrix.sort_values(ascending=False)\n",
    "print(sorted_corr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yGeFTN0Cebju"
   },
   "source": [
    "#Plotted the Sorted Corelation Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 872
    },
    "id": "WKsuTz2dJ96S",
    "outputId": "cf645356-50f7-4baf-f401-13d4f3891bc2"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15, 10))\n",
    "sns.barplot(x=sorted_corr.values, y=sorted_corr.index)\n",
    "plt.title('Correlation with Decision')\n",
    "plt.xlabel('Correlation Coefficient')\n",
    "plt.ylabel('Features')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "CRSGsqfnebju"
   },
   "source": [
    "#Creating new DF with only relevant columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "J_M-Jt0BJ96S",
    "outputId": "c6948ba5-5217-436d-91c2-96a684e1bbcb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Decision', 'Time_bank', 'Time_employed', 'Balance', 'Age',\n",
      "       'Occupation_professio', 'Time_at_address', 'Job_status_governmen',\n",
      "       'Telephone_given', 'Res_status_owner', 'Occupation_semi_pro',\n",
      "       'Occupation_office_st', 'Acc_ref_given', 'Job_status_retired',\n",
      "       'Liab_ref_t', 'Occupation_executive', 'Sex_F', 'Occupation_creative_',\n",
      "       'Occupation_productio'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "positive_corr_cols = sorted_corr[sorted_corr > 0].index\n",
    "df = df.loc[:, positive_corr_cols]\n",
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-c2f0RJ-J96S"
   },
   "source": [
    "#Plotting the graphs for above columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "EG8zvtueT8qZ",
    "outputId": "0154fe6e-4d7e-436f-f2fc-13bb33cf8c89"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Decision', 'Time_bank', 'Time_employed', 'Balance', 'Age',\n",
       "       'Occupation_professio', 'Time_at_address', 'Job_status_governmen',\n",
       "       'Telephone_given', 'Res_status_owner', 'Occupation_semi_pro',\n",
       "       'Occupation_office_st', 'Acc_ref_given', 'Job_status_retired',\n",
       "       'Liab_ref_t', 'Occupation_executive', 'Sex_F', 'Occupation_creative_',\n",
       "       'Occupation_productio'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Xt2u-hB1ebjv"
   },
   "source": [
    "#plotted the Relevant Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 607
    },
    "id": "AdcTIY8IUfjx",
    "outputId": "c0b31e3c-12f9-478b-b24e-aa535e44b1db"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "columns_to_plot = ['Decision', 'Time_bank', 'Time_employed', 'Balance', 'Age','Occupation_professio', 'Time_at_address', 'Job_status_governmen','Telephone_given', 'Res_status_owner', 'Occupation_semi_pro',                   \n",
    "                   'Occupation_office_st', 'Acc_ref_given', 'Job_status_retired','Liab_ref_t', 'Occupation_executive', 'Sex_F', 'Occupation_creative_','Occupation_productio']\n",
    "columns_set = ['Decision', 'Time_bank', 'Time_employed', 'Occupation_professio']\n",
    "plt.figure(figsize=(10,6))\n",
    "for i, column in enumerate(columns_set):\n",
    "    plt.subplot(2,3,i+1)\n",
    "    df.groupby(column)[column].count().plot(kind='bar', color='blue')\n",
    "    plt.title(column)\n",
    "    plt.xlabel(column)\n",
    "    plt.ylabel(\"Count\")\n",
    "    plt.xticks(rotation=45)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ibhCN6zwJ96T"
   },
   "source": [
    "#Split the data into X and y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "tDABKGy3J96T",
    "outputId": "6add35e2-3e04-473f-8968-1b16324464cb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['Time_bank', 'Time_employed', 'Balance', 'Age', 'Occupation_professio',\n",
      "       'Time_at_address', 'Job_status_governmen', 'Telephone_given',\n",
      "       'Res_status_owner', 'Occupation_semi_pro', 'Occupation_office_st',\n",
      "       'Acc_ref_given', 'Job_status_retired', 'Liab_ref_t',\n",
      "       'Occupation_executive', 'Sex_F', 'Occupation_creative_',\n",
      "       'Occupation_productio'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "X = df.drop('Decision', axis=1)\n",
    "y = df['Decision']\n",
    "print(X.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "phWF0MQ1J96T",
    "outputId": "1453541e-9267-4772-eb65-b2178f6d2223"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    0\n",
      "1    0\n",
      "2    1\n",
      "3    1\n",
      "4    0\n",
      "Name: Decision, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(y.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "FvI8gIIUebjw"
   },
   "source": [
    "#Normalizing the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "id": "M9s7Cy4cJ96U"
   },
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=21)\n",
    "scaler = MinMaxScaler()\n",
    "X_train = scaler.fit_transform(X_train)\n",
    "X_test = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "VcvBfvdYJ96U",
    "outputId": "7f58c3d6-8476-4476-d887-878c23294a56"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X_train shape: (343, 18)\n",
      "X_test shape: (86, 18)\n",
      "y_train shape: (343,)\n",
      "y_test shape: (86,)\n"
     ]
    }
   ],
   "source": [
    "print(\"X_train shape:\", X_train.shape)\n",
    "print(\"X_test shape:\", X_test.shape)\n",
    "print(\"y_train shape:\", y_train.shape)\n",
    "print(\"y_test shape:\", y_test.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ZRv_LI4aebjw"
   },
   "source": [
    "#Applied NN model with 4 Layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "kwqHK1ktJ96U"
   },
   "outputs": [],
   "source": [
    "model = Sequential()\n",
    "model.add(Dense(32, input_dim=X_train.shape[1], activation='relu'))\n",
    "model.add(Dropout(0.2))\n",
    "model.add(Dense(32, activation='relu'))\n",
    "model.add(Dropout(0.2))\n",
    "model.add(Dense(32, activation='relu'))\n",
    "model.add(Dense(16, activation='relu'))\n",
    "model.add(Dropout(0.2))\n",
    "model.add(Dense(1, activation='sigmoid'))\n",
    "model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "3QOadO8dJ96U"
   },
   "outputs": [],
   "source": [
    "# class CustomCallback(tf.keras.callbacks.Callback):\n",
    "#     def on_train_batch_begin(self, batch, logs=None):\n",
    "#         print(model.get_weights())\n",
    "#         keys = list(logs.keys())\n",
    "#         print(\"...Training: start of batch {}; got log keys: {}\".format(batch, keys))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "7017_hq-J96U"
   },
   "outputs": [],
   "source": [
    "from keras.callbacks import EarlyStopping\n",
    "early_stopping = EarlyStopping(monitor='val_loss', patience=10, restore_best_weights=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "31JRITx0ebjw"
   },
   "source": [
    "#Fit the model on the training data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "D1Lt7_QVJ96U",
    "outputId": "f7466bf2-840b-4b59-8b72-3292c2edab0c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/500\n",
      "22/22 [==============================] - 3s 24ms/step - loss: 0.7080 - accuracy: 0.5044 - val_loss: 0.6963 - val_accuracy: 0.4884\n",
      "Epoch 2/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.6912 - accuracy: 0.5306 - val_loss: 0.6928 - val_accuracy: 0.6047\n",
      "Epoch 3/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.6904 - accuracy: 0.5219 - val_loss: 0.6921 - val_accuracy: 0.5349\n",
      "Epoch 4/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.6872 - accuracy: 0.5802 - val_loss: 0.6885 - val_accuracy: 0.5581\n",
      "Epoch 5/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.6910 - accuracy: 0.5335 - val_loss: 0.6817 - val_accuracy: 0.5930\n",
      "Epoch 6/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.6682 - accuracy: 0.6152 - val_loss: 0.6763 - val_accuracy: 0.5930\n",
      "Epoch 7/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.6567 - accuracy: 0.6297 - val_loss: 0.6698 - val_accuracy: 0.5698\n",
      "Epoch 8/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.6625 - accuracy: 0.6093 - val_loss: 0.6608 - val_accuracy: 0.6047\n",
      "Epoch 9/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.6353 - accuracy: 0.6764 - val_loss: 0.6390 - val_accuracy: 0.6163\n",
      "Epoch 10/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.6217 - accuracy: 0.6239 - val_loss: 0.6214 - val_accuracy: 0.6744\n",
      "Epoch 11/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.6068 - accuracy: 0.6676 - val_loss: 0.6117 - val_accuracy: 0.6395\n",
      "Epoch 12/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5772 - accuracy: 0.7085 - val_loss: 0.5941 - val_accuracy: 0.6163\n",
      "Epoch 13/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5599 - accuracy: 0.7376 - val_loss: 0.5824 - val_accuracy: 0.6512\n",
      "Epoch 14/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5720 - accuracy: 0.7085 - val_loss: 0.5713 - val_accuracy: 0.6512\n",
      "Epoch 15/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.5373 - accuracy: 0.7405 - val_loss: 0.5627 - val_accuracy: 0.6744\n",
      "Epoch 16/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5500 - accuracy: 0.7318 - val_loss: 0.5498 - val_accuracy: 0.6860\n",
      "Epoch 17/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5426 - accuracy: 0.7230 - val_loss: 0.5476 - val_accuracy: 0.6744\n",
      "Epoch 18/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5337 - accuracy: 0.7347 - val_loss: 0.5490 - val_accuracy: 0.6977\n",
      "Epoch 19/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5142 - accuracy: 0.7638 - val_loss: 0.5363 - val_accuracy: 0.6628\n",
      "Epoch 20/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.5174 - accuracy: 0.7493 - val_loss: 0.5313 - val_accuracy: 0.6744\n",
      "Epoch 21/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5346 - accuracy: 0.7522 - val_loss: 0.5272 - val_accuracy: 0.6977\n",
      "Epoch 22/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.5030 - accuracy: 0.7609 - val_loss: 0.5296 - val_accuracy: 0.6860\n",
      "Epoch 23/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4985 - accuracy: 0.7668 - val_loss: 0.5321 - val_accuracy: 0.6744\n",
      "Epoch 24/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.4877 - accuracy: 0.7638 - val_loss: 0.5227 - val_accuracy: 0.6977\n",
      "Epoch 25/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.4851 - accuracy: 0.7726 - val_loss: 0.5170 - val_accuracy: 0.7209\n",
      "Epoch 26/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.4984 - accuracy: 0.7872 - val_loss: 0.5149 - val_accuracy: 0.6977\n",
      "Epoch 27/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4939 - accuracy: 0.7813 - val_loss: 0.5109 - val_accuracy: 0.7209\n",
      "Epoch 28/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4754 - accuracy: 0.7755 - val_loss: 0.5052 - val_accuracy: 0.7093\n",
      "Epoch 29/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4812 - accuracy: 0.7813 - val_loss: 0.5082 - val_accuracy: 0.7209\n",
      "Epoch 30/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4973 - accuracy: 0.7726 - val_loss: 0.5000 - val_accuracy: 0.7442\n",
      "Epoch 31/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4574 - accuracy: 0.7843 - val_loss: 0.4990 - val_accuracy: 0.7093\n",
      "Epoch 32/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4746 - accuracy: 0.7959 - val_loss: 0.5001 - val_accuracy: 0.7326\n",
      "Epoch 33/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4702 - accuracy: 0.7755 - val_loss: 0.5028 - val_accuracy: 0.7442\n",
      "Epoch 34/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.4973 - accuracy: 0.7872 - val_loss: 0.5018 - val_accuracy: 0.7558\n",
      "Epoch 35/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4534 - accuracy: 0.7872 - val_loss: 0.4976 - val_accuracy: 0.7442\n",
      "Epoch 36/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.4497 - accuracy: 0.7959 - val_loss: 0.5023 - val_accuracy: 0.7442\n",
      "Epoch 37/500\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 0.4485 - accuracy: 0.8192 - val_loss: 0.4985 - val_accuracy: 0.7674\n",
      "Epoch 38/500\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 0.4422 - accuracy: 0.8047 - val_loss: 0.5064 - val_accuracy: 0.7326\n",
      "Epoch 39/500\n",
      "22/22 [==============================] - 0s 8ms/step - loss: 0.4190 - accuracy: 0.8251 - val_loss: 0.5050 - val_accuracy: 0.7326\n",
      "Epoch 40/500\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 0.4447 - accuracy: 0.8163 - val_loss: 0.5021 - val_accuracy: 0.7442\n",
      "Epoch 41/500\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 0.4106 - accuracy: 0.8338 - val_loss: 0.4989 - val_accuracy: 0.7558\n",
      "Epoch 42/500\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 0.4598 - accuracy: 0.7988 - val_loss: 0.4943 - val_accuracy: 0.7674\n",
      "Epoch 43/500\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 0.4131 - accuracy: 0.8076 - val_loss: 0.4957 - val_accuracy: 0.7558\n",
      "Epoch 44/500\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 0.4148 - accuracy: 0.8338 - val_loss: 0.5044 - val_accuracy: 0.7442\n",
      "Epoch 45/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.4192 - accuracy: 0.8222 - val_loss: 0.5039 - val_accuracy: 0.7442\n",
      "Epoch 46/500\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 0.4075 - accuracy: 0.8309 - val_loss: 0.5091 - val_accuracy: 0.7326\n",
      "Epoch 47/500\n",
      "22/22 [==============================] - 0s 7ms/step - loss: 0.4309 - accuracy: 0.7988 - val_loss: 0.5066 - val_accuracy: 0.7791\n",
      "Epoch 48/500\n",
      "22/22 [==============================] - 0s 8ms/step - loss: 0.4314 - accuracy: 0.8309 - val_loss: 0.5009 - val_accuracy: 0.7674\n",
      "Epoch 49/500\n",
      "22/22 [==============================] - 0s 19ms/step - loss: 0.4466 - accuracy: 0.8192 - val_loss: 0.5035 - val_accuracy: 0.7674\n",
      "Epoch 50/500\n",
      "22/22 [==============================] - 0s 15ms/step - loss: 0.3991 - accuracy: 0.8192 - val_loss: 0.5042 - val_accuracy: 0.7674\n",
      "Epoch 51/500\n",
      "22/22 [==============================] - 0s 16ms/step - loss: 0.4078 - accuracy: 0.8309 - val_loss: 0.5071 - val_accuracy: 0.7674\n",
      "Epoch 52/500\n",
      "22/22 [==============================] - 0s 22ms/step - loss: 0.3936 - accuracy: 0.8251 - val_loss: 0.5102 - val_accuracy: 0.7674\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "history = model.fit(X_train, y_train, epochs=500, batch_size=16, validation_data=(X_test, y_test), callbacks=[early_stopping])\n",
    "plt.plot(history.history['loss'], label='Training Loss')\n",
    "plt.plot(history.history['val_loss'], label='Validation Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "plt.plot(history.history['accuracy'], label='Training Accuracy')\n",
    "plt.plot(history.history['val_accuracy'], label='Validation Accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "7W7O8Sigebjx"
   },
   "source": [
    "#Evaluate the model on the test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "LivUBLrxJ96U",
    "outputId": "b0ce2c4d-89fa-4448-8ab5-a482382a5a38"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Accuracy: 84.26%\n"
     ]
    }
   ],
   "source": [
    "loss, accuracy = model.evaluate(X_train, y_train, verbose=0)\n",
    "print(\"Training Accuracy: {:.2f}%\".format(accuracy*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "zdoPGZ0TJ96U",
    "outputId": "30d86e10-7f50-4078-9702-4df572a14739"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Loss: 0.4942989647388458\n",
      "Test Accuracy: 0.7674418687820435\n"
     ]
    }
   ],
   "source": [
    "test_loss, test_accuracy = model.evaluate(X_test, y_test,verbose=0)\n",
    "print('Test Loss:', test_loss)\n",
    "print('Test Accuracy:', test_accuracy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "yWj7H0pWebjx"
   },
   "source": [
    "#Applied NN with 2 layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "id": "Q21KIXxqJ96U"
   },
   "outputs": [],
   "source": [
    "model_new= Sequential()\n",
    "model_new.add(Dense(24,activation='relu',input_dim=X_train.shape[1]))\n",
    "model_new.add(Dense(12,activation='relu'))\n",
    "model_new.add(Dense(1,activation='sigmoid'))\n",
    "model_new.compile(optimizer='adam',loss='binary_crossentropy',metrics=['accuracy'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "2BdJrPj4J96U",
    "outputId": "85feda76-270b-4c18-afbf-ef9bd2c14ce4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "43/43 [==============================] - 1s 7ms/step - loss: 0.7016 - accuracy: 0.4723 - val_loss: 0.7046 - val_accuracy: 0.4186\n",
      "Epoch 2/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.6771 - accuracy: 0.6181 - val_loss: 0.6890 - val_accuracy: 0.5698\n",
      "Epoch 3/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.6649 - accuracy: 0.6880 - val_loss: 0.6783 - val_accuracy: 0.6047\n",
      "Epoch 4/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.6525 - accuracy: 0.7085 - val_loss: 0.6692 - val_accuracy: 0.5930\n",
      "Epoch 5/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.6349 - accuracy: 0.7376 - val_loss: 0.6556 - val_accuracy: 0.6163\n",
      "Epoch 6/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.6149 - accuracy: 0.7522 - val_loss: 0.6347 - val_accuracy: 0.6628\n",
      "Epoch 7/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.5927 - accuracy: 0.7493 - val_loss: 0.6131 - val_accuracy: 0.6744\n",
      "Epoch 8/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.5726 - accuracy: 0.7697 - val_loss: 0.5943 - val_accuracy: 0.7093\n",
      "Epoch 9/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.5460 - accuracy: 0.7668 - val_loss: 0.5713 - val_accuracy: 0.7791\n",
      "Epoch 10/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.5262 - accuracy: 0.7843 - val_loss: 0.5517 - val_accuracy: 0.7326\n",
      "Epoch 11/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.5100 - accuracy: 0.7843 - val_loss: 0.5401 - val_accuracy: 0.7907\n",
      "Epoch 12/100\n",
      "43/43 [==============================] - 0s 4ms/step - loss: 0.4962 - accuracy: 0.7901 - val_loss: 0.5235 - val_accuracy: 0.7791\n",
      "Epoch 13/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4859 - accuracy: 0.7872 - val_loss: 0.5146 - val_accuracy: 0.7558\n",
      "Epoch 14/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4759 - accuracy: 0.8017 - val_loss: 0.5110 - val_accuracy: 0.8140\n",
      "Epoch 15/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4689 - accuracy: 0.7872 - val_loss: 0.5018 - val_accuracy: 0.8256\n",
      "Epoch 16/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4631 - accuracy: 0.8017 - val_loss: 0.4951 - val_accuracy: 0.8140\n",
      "Epoch 17/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4576 - accuracy: 0.7930 - val_loss: 0.4933 - val_accuracy: 0.8256\n",
      "Epoch 18/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4544 - accuracy: 0.7872 - val_loss: 0.4908 - val_accuracy: 0.8256\n",
      "Epoch 19/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4501 - accuracy: 0.7988 - val_loss: 0.4948 - val_accuracy: 0.7907\n",
      "Epoch 20/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4468 - accuracy: 0.7959 - val_loss: 0.4818 - val_accuracy: 0.8256\n",
      "Epoch 21/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4434 - accuracy: 0.7930 - val_loss: 0.4818 - val_accuracy: 0.8140\n",
      "Epoch 22/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4426 - accuracy: 0.7959 - val_loss: 0.4781 - val_accuracy: 0.8140\n",
      "Epoch 23/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4364 - accuracy: 0.8017 - val_loss: 0.4779 - val_accuracy: 0.8140\n",
      "Epoch 24/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4378 - accuracy: 0.7988 - val_loss: 0.4802 - val_accuracy: 0.7907\n",
      "Epoch 25/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4326 - accuracy: 0.8017 - val_loss: 0.4763 - val_accuracy: 0.8256\n",
      "Epoch 26/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4332 - accuracy: 0.8076 - val_loss: 0.4780 - val_accuracy: 0.8140\n",
      "Epoch 27/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4234 - accuracy: 0.8017 - val_loss: 0.4756 - val_accuracy: 0.8256\n",
      "Epoch 28/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4231 - accuracy: 0.8017 - val_loss: 0.4773 - val_accuracy: 0.8256\n",
      "Epoch 29/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4230 - accuracy: 0.8047 - val_loss: 0.4780 - val_accuracy: 0.7907\n",
      "Epoch 30/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4200 - accuracy: 0.8105 - val_loss: 0.4900 - val_accuracy: 0.7674\n",
      "Epoch 31/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4174 - accuracy: 0.8047 - val_loss: 0.4783 - val_accuracy: 0.8140\n",
      "Epoch 32/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4236 - accuracy: 0.8134 - val_loss: 0.4809 - val_accuracy: 0.8256\n",
      "Epoch 33/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4122 - accuracy: 0.8105 - val_loss: 0.4805 - val_accuracy: 0.8256\n",
      "Epoch 34/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4122 - accuracy: 0.8192 - val_loss: 0.4799 - val_accuracy: 0.8023\n",
      "Epoch 35/100\n",
      "43/43 [==============================] - 0s 3ms/step - loss: 0.4108 - accuracy: 0.8134 - val_loss: 0.4794 - val_accuracy: 0.8140\n",
      "Epoch 36/100\n",
      "43/43 [==============================] - 0s 6ms/step - loss: 0.4070 - accuracy: 0.8105 - val_loss: 0.4803 - val_accuracy: 0.8140\n",
      "Epoch 37/100\n",
      "43/43 [==============================] - 0s 6ms/step - loss: 0.4035 - accuracy: 0.8163 - val_loss: 0.4844 - val_accuracy: 0.8023\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "history2 = model_new.fit(X_train, y_train, epochs=100, batch_size=8, validation_data=(X_test, y_test), callbacks=[early_stopping])\n",
    "plt.plot(history2.history['loss'], label='Training Loss')\n",
    "plt.plot(history2.history['val_loss'], label='Validation Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Loss')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "plt.plot(history2.history['accuracy'], label='Training Accuracy')\n",
    "plt.plot(history2.history['val_accuracy'], label='Validation Accuracy')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NySJf8U1ebjx"
   },
   "source": [
    "#Evaluate the model on the test data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "GreoTR44J96U",
    "outputId": "e345d956-86f8-49a9-ab4d-e5d8462aee3b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3/3 [==============================] - 0s 4ms/step - loss: 0.4756 - accuracy: 0.8256\n",
      "Accuracy: 82.56%\n"
     ]
    }
   ],
   "source": [
    "loss, accuracy = model_new.evaluate(X_test, y_test, verbose=1)\n",
    "print(\"Accuracy: {:.2f}%\".format(accuracy*100))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5L8hpBxKebjy"
   },
   "source": [
    "#Weight Analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 807
    },
    "id": "-Gh0YeFiJ96V",
    "outputId": "adbc38cd-5456-4356-d228-85190f2493cb"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "weights1 = model_new.layers[0].get_weights()[0]\n",
    "fig, axs = plt.subplots(2, 2, figsize=(12, 8))\n",
    "axs[0, 0].imshow(weights1, cmap='coolwarm')\n",
    "axs[0, 0].set_title('Weights of First Dense Layer')\n",
    "axs[0, 0].axis('off')\n",
    "axs[0, 1].hist(weights1.flatten(), bins=20, color='blue', alpha=0.5)\n",
    "axs[0, 1].set_xlabel('Weight Value')\n",
    "axs[0, 1].set_ylabel('Frequency')\n",
    "axs[0, 1].set_title('Histogram of Weights of First Dense Layer')\n",
    "weights2 = model_new.layers[1].get_weights()[0]\n",
    "axs[1, 0].imshow(weights2, cmap='coolwarm')\n",
    "axs[1, 0].set_title('Weights of Second Dense Layer')\n",
    "axs[1, 0].axis('off')\n",
    "axs[1, 1].hist(weights2.flatten(), bins=20, color='blue', alpha=0.5)\n",
    "axs[1, 1].set_xlabel('Weight Value')\n",
    "axs[1, 1].set_ylabel('Frequency')\n",
    "axs[1, 1].set_title('Histogram of Weights of Second Dense Layer')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "YwXdWzGpebjy"
   },
   "source": [
    "#ROC Curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 489
    },
    "id": "W1NvvWgoJ96V",
    "outputId": "5f53d40d-4697-4e1f-ccfb-f7544d349f8e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3/3 [==============================] - 0s 5ms/step\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import roc_curve, auc\n",
    "y_score = model_new.predict(X_test)\n",
    "fpr, tpr, thresholds = roc_curve(y_test.ravel(), y_score.ravel())\n",
    "roc_auc = auc(fpr, tpr)\n",
    "plt.plot(fpr, tpr, lw=1, label='ROC (AUC = %0.2f)' % roc_auc)\n",
    "plt.plot([0, 1], [0, 1], linestyle='--', lw=1, color='gray')\n",
    "plt.xlabel('False Positive Rate')\n",
    "plt.ylabel('True Positive Rate')\n",
    "plt.title('Receiver Operating Characteristic (ROC) Curve')\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  },
  "vscode": {
   "interpreter": {
    "hash": "b0fa6594d8f4cbf19f97940f81e996739fb7646882a419484c72d19e05852a7e"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}