Python Programming

find the correlation between ‘survived’ (target column) and ‘sex’ column for the Titanic use case in class.Do you think we should keep this feature?

Implement Naïve Bayes method using scikit-learn library

Use dataset available in Data Set

Use train_test_split to create training and testing part

Evaluate the model on testing part using score and classification_report(y_true, y_pred)

Implement linear SVM method using scikit library

Use the same dataset above

Use train_test_split to create training and testing part

Evaluate the model on testing part using score and classification_report(y_true, y_pred)

Which algorithm you got better accuracy? Can you justify why?