•The goal is predict status of customer using loan and customer information.
•It
includes tasks such as data visualization, cleaning, transformation, feature
engineering.
•The ensemble learning techniques such as voting, boosting,
bagging are used.
•In this case in voting decision tree, logistic regression,
support vector machine are used as base learners.
•The random forest
(bagging), Gradient boosting (boosting) are used, voting method gives better
performance.
•Libraries used are sklearn, matplotlib, pandas, and numpy.