"C:\Users\hp\Downloads\Logistic regression based on Binary classification.ipynb"

In this case, we are using Logistic Regression to predict the prediction. Here, when we are doing analysis then we find out that ma is not in integer form then we first convert ma into integer. After that we use is null in Python to find out any null here or not, we found there is a null present then we will just use dropna () to drop null. We define the training dataset and testing dataset(we assume training = 0.7 & testing = 0.3) also we standardize the data by Standard Scaler for better accuracy Finally, accuracy will be found log_reg.score(X_train_scaled,y_train) = 0.7867425870219167 log_reg.score(X_test_scaled,y_test) = 0.7839598997493734