6.3-NaiveBayes.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"NaiveBayes.ipynb","provenance":[],"authorship_tag":"ABX9TyPSKHPK/yroYzfx+bYOiC5J"},"kernelspec":{"name":"python3","display_name":"Python 3"}},"cells":[{"cell_type":"code","metadata":{"id":"aovqmtEbaWPT","colab_type":"code","colab":{}},"source":["import numpy as np\n","import pandas as pd\n","from sklearn.model_selection import train_test_split\n","from sklearn.naive_bayes import GaussianNB\n","from sklearn import metrics\n","from sklearn.metrics import classification_report\n","from sklearn.metrics import confusion_matrix,accuracy_score\n","from sklearn.metrics import accuracy_score\n","import matplotlib.pyplot as plt\n","import seaborn as sns"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"zjW6WIjCbaOh","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":200},"outputId":"cb10e877-87f8-4106-cec5-ce91ca3032af","executionInfo":{"status":"ok","timestamp":1589649510458,"user_tz":-360,"elapsed":906,"user":{"displayName":"Fazly Rabbi Khan","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhMXAHw3161kgjaCR7P1g9H9jC98PuMWQQDNeNmMQ=s64","userId":"01152345321765059291"}}},"source":["url='https://raw.githubusercontent.com/FazlyRabbiBD/Data-Science-Book/master/data-diabetes.csv'\n","df = pd.read_csv(url)\n","df.head()"],"execution_count":4,"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>glucose</th>\n","      <th>bloodpressure</th>\n","      <th>diabetes</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>40</td>\n","      <td>85</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>40</td>\n","      <td>92</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>45</td>\n","      <td>63</td>\n","      <td>1</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>45</td>\n","      <td>80</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>40</td>\n","      <td>73</td>\n","      <td>1</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["   glucose  bloodpressure  diabetes\n","0       40             85         0\n","1       40             92         0\n","2       45             63         1\n","3       45             80         0\n","4       40             73         1"]},"metadata":{"tags":[]},"execution_count":4}]},{"cell_type":"code","metadata":{"id":"LTsf1TdwfkWb","colab_type":"code","colab":{}},"source":["features=['glucose','bloodpressure']\n","x=df[features]\n","y=df.diabetes"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"yvutfjyofmZQ","colab_type":"code","colab":{}},"source":["x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.25, random_state=5)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"rXaqrIvTgqpm","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":35},"outputId":"bb74e4ac-be34-4a8f-8c57-2b65d7261441","executionInfo":{"status":"ok","timestamp":1589649905064,"user_tz":-360,"elapsed":1304,"user":{"displayName":"Fazly Rabbi Khan","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhMXAHw3161kgjaCR7P1g9H9jC98PuMWQQDNeNmMQ=s64","userId":"01152345321765059291"}}},"source":["model=GaussianNB()\n","model.fit(x_train,y_train)"],"execution_count":7,"outputs":[{"output_type":"execute_result","data":{"text/plain":["GaussianNB(priors=None, var_smoothing=1e-09)"]},"metadata":{"tags":[]},"execution_count":7}]},{"cell_type":"code","metadata":{"id":"DuY7Jah1hJAO","colab_type":"code","colab":{}},"source":["predictions = model.predict(x_test)"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"qM6ItbTvhubF","colab_type":"code","colab":{}},"source":["from sklearn import metrics\n","from sklearn.metrics import classification_report\n","from sklearn.metrics import confusion_matrix,accuracy_score\n","from sklearn.metrics import roc_auc_score\n","from sklearn.metrics import roc_curve"],"execution_count":0,"outputs":[]},{"cell_type":"code","metadata":{"id":"_R0FewR9hSts","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":301},"outputId":"85e47d73-a0f4-4c53-c923-0597e6c5a079","executionInfo":{"status":"ok","timestamp":1589651994258,"user_tz":-360,"elapsed":2655,"user":{"displayName":"Fazly Rabbi Khan","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhMXAHw3161kgjaCR7P1g9H9jC98PuMWQQDNeNmMQ=s64","userId":"01152345321765059291"}}},"source":["#Model performance Report\n","\n"," \n","print('Classification Report:\\n',classification_report(y_test, predictions))\n","print('Confusion Matrix:\\n',confusion_matrix(y_test, predictions))\n","print('Accuracy Score:',accuracy_score(y_test, predictions))\n","print(\"Precision:\",metrics.precision_score(y_test, predictions))\n","print(\"Recall:\",metrics.recall_score(y_test,predictions ))"],"execution_count":16,"outputs":[{"output_type":"stream","text":["Classification Report:\n","               precision    recall  f1-score   support\n","\n","           0       0.97      0.92      0.94       123\n","           1       0.92      0.97      0.95       126\n","\n","    accuracy                           0.94       249\n","   macro avg       0.95      0.94      0.94       249\n","weighted avg       0.94      0.94      0.94       249\n","\n","Confusion Matrix:\n"," [[113  10]\n"," [  4 122]]\n","Accuracy Score: 0.9437751004016064\n","Precision: 0.9242424242424242\n","Recall: 0.9682539682539683\n"],"name":"stdout"}]},{"cell_type":"code","metadata":{"id":"4S9Aa0Hwhdhd","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":35},"outputId":"c353b004-5bca-4269-dddb-d4b7ae07fc15","executionInfo":{"status":"ok","timestamp":1589654603311,"user_tz":-360,"elapsed":1055,"user":{"displayName":"Fazly Rabbi Khan","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhMXAHw3161kgjaCR7P1g9H9jC98PuMWQQDNeNmMQ=s64","userId":"01152345321765059291"}}},"source":["new_observation = [[40,65]]\n","model.predict(new_observation)"],"execution_count":22,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([1])"]},"metadata":{"tags":[]},"execution_count":22}]},{"cell_type":"code","metadata":{"id":"YJ8Sp8_zygU3","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":35},"outputId":"87a4278f-05a3-4319-d7bf-1860ef9a70c3","executionInfo":{"status":"ok","timestamp":1589654529385,"user_tz":-360,"elapsed":852,"user":{"displayName":"Fazly Rabbi Khan","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14GhMXAHw3161kgjaCR7P1g9H9jC98PuMWQQDNeNmMQ=s64","userId":"01152345321765059291"}}},"source":["model.predict_proba(new_observation)"],"execution_count":18,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[2.88884850e-04, 9.99711115e-01]])"]},"metadata":{"tags":[]},"execution_count":18}]},{"cell_type":"code","metadata":{"id":"scCFNaA6yyE4","colab_type":"code","colab":{}},"source":[""],"execution_count":0,"outputs":[]}]}