Classification Model

Analyzed the data. Made some graphs to get some inferences .For ex:-the data was highly imbalanced with respected to the predicted values, the data distribution was very symmetrical with respect to the features. Under Sampled the data and replaced the missing values with mean. Scaled the data using standard scaler. Made several classification models along with their hyperparameter tuning and made classification report of all of them. Eventually found that the one with the highest f1 score is Logistic regression , so applied that on the Test Data and got the results.