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code.py
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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Untitled0.ipynb",
"provenance": [],
"collapsed_sections": [],
"authorship_tag": "ABX9TyNTv1SGUKSGpt4kl/XEwKm7",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/DeepankarGupta13/Diabetes-Prediction-ussing-Naive-Bayes-/blob/main/code.py\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"metadata": {
"id": "ynPB0ZYOp2lh"
},
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"from sklearn.model_selection import train_test_split\n",
"from sklearn.preprocessing import StandardScaler\n",
"from sklearn.naive_bayes import GaussianNB\n",
"from sklearn.metrics import confusion_matrix\n",
"from sklearn.metrics import f1_score\n",
"from sklearn.metrics import accuracy_score\n",
"from sklearn.feature_selection import SelectKBest\n",
"from sklearn.feature_selection import chi2\n",
"from sklearn.feature_selection import VarianceThreshold\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"%matplotlib inline"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "-dQndxc8p8wn"
},
"source": [
"dataset = pd.read_csv('/content/diabetes.csv')"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "p4mkhuffqBz-",
"outputId": "6ac72359-a612-437e-a5d2-b2a322658332"
},
"source": [
"print(dataset.describe())\n",
"X = dataset.iloc[:, 0:8]\n",
"y = dataset.iloc[:, 8]"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
" Pregnancies Glucose ... Age Outcome\n",
"count 768.000000 768.000000 ... 768.000000 768.000000\n",
"mean 3.845052 120.894531 ... 33.240885 0.348958\n",
"std 3.369578 31.972618 ... 11.760232 0.476951\n",
"min 0.000000 0.000000 ... 21.000000 0.000000\n",
"25% 1.000000 99.000000 ... 24.000000 0.000000\n",
"50% 3.000000 117.000000 ... 29.000000 0.000000\n",
"75% 6.000000 140.250000 ... 41.000000 1.000000\n",
"max 17.000000 199.000000 ... 81.000000 1.000000\n",
"\n",
"[8 rows x 9 columns]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 407
},
"id": "wvUmWE03qNge",
"outputId": "4843fa97-5202-4c6f-dcbf-8f1539f81e4e"
},
"source": [
"sns.heatmap(X.corr(), annot = True)"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7fa5510b3d90>"
]
},
"metadata": {
"tags": []
},
"execution_count": 6
},
{
"output_type": "display_data",
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "mbdVIV1NqSke"
},
"source": [
"zero_not_accepted = ['Glucose', 'BloodPressure', 'SkinThickness', 'BMI', 'Insulin']\n",
"for column in zero_not_accepted:\n",
" X[column] = X[column].replace(0, np.NaN)\n",
" mean = int(X[column].mean(skipna=True))\n",
" X[column] = X[column].replace(np.NaN, mean)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "voLi-uOmqYPv",
"outputId": "5176ef86-b2f3-42dd-9c09-8106adb0fd63"
},
"source": [
"## Var[X] = p(1-p)\n",
"sel = VarianceThreshold(threshold=(.8 * (1 - .8)))\n",
"X_filtered = sel.fit_transform(X)\n",
"\n",
"print(X.head(1))\n",
"print(X_filtered[0])\n",
"#DiabetesPedigreeFunction was dropped\n",
"X = X.drop('DiabetesPedigreeFunction', axis=1)\n",
"\n",
"top_4_features = SelectKBest(score_func=chi2, k=4)\n",
"X_top_4_features = top_4_features.fit_transform(X, y)\n",
"print(X.head())\n",
"print(X_top_4_features)\n",
"X = X.drop(['Pregnancies', 'BloodPressure', 'SkinThickness'], axis=1)"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
" Pregnancies Glucose BloodPressure ... BMI DiabetesPedigreeFunction Age\n",
"0 6 148.0 72.0 ... 33.6 0.627 50\n",
"\n",
"[1 rows x 8 columns]\n",
"[ 6. 148. 72. 35. 155. 33.6 50. ]\n",
" Pregnancies Glucose BloodPressure SkinThickness Insulin BMI Age\n",
"0 6 148.0 72.0 35.0 155.0 33.6 50\n",
"1 1 85.0 66.0 29.0 155.0 26.6 31\n",
"2 8 183.0 64.0 29.0 155.0 23.3 32\n",
"3 1 89.0 66.0 23.0 94.0 28.1 21\n",
"4 0 137.0 40.0 35.0 168.0 43.1 33\n",
"[[ 6. 148. 155. 50.]\n",
" [ 1. 85. 155. 31.]\n",
" [ 8. 183. 155. 32.]\n",
" ...\n",
" [ 5. 121. 112. 30.]\n",
" [ 1. 126. 155. 47.]\n",
" [ 1. 93. 155. 23.]]\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "R5ALnZNZq5oV"
},
"source": [
"X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0, test_size=0.20)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "qkWMJid4q-m_"
},
"source": [
"sc_X = StandardScaler()\n",
"X_train = sc_X.fit_transform(X_train)\n",
"X_test = sc_X.transform(X_test)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "p1zMhSN8rBL2",
"outputId": "70981d15-a2ce-4793-d84b-b43f9c8ccefe"
},
"source": [
"classifier = GaussianNB()\n",
"classifier.fit(X_train, y_train)"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"GaussianNB(priors=None, var_smoothing=1e-09)"
]
},
"metadata": {
"tags": []
},
"execution_count": 13
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "snnIbQ-3rFcm"
},
"source": [
"y_pred = classifier.predict(X_test)"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "obcefER9rHwO",
"outputId": "4573754f-10dc-4494-d067-0579bebff7f5"
},
"source": [
"cm = confusion_matrix(y_test, y_pred)\n",
"print (cm)\n",
"print(f1_score(y_test, y_pred))\n",
"print(accuracy_score(y_test, y_pred))"
],
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"text": [
"[[96 11]\n",
" [21 26]]\n",
"0.6190476190476191\n",
"0.7922077922077922\n"
],
"name": "stdout"
}
]
}
]
}