Loan Prediction 3: Reveal Your Approach

r
machine_learning
python

#1

Hello,

Now that the contest is over please reveal your approach for Loan Prediction III. It seems the public leader board score is stuck with some discrete values. I’ve go score of 0.791667. I performed some feature engineering like log transformation of big values instead of scaling, creating features like monthly loan amount from Loan_Amount_Term & LoanAmount. And some other feature engineering too. I used an ensemble model of XGboost, Random Forest and Adaboost. I got my maximum cross validation score with StatifiedKFold of ~ 89% and without KFold of ~ 83%. I shall upload the code soon for all the beginners. Please share your approach and code for all who got better score. Also do you guys think it was more of a feature engineering problem?


#2

Contest not over yet…date has been extended till dec end


#3

Yes I saw that now…when I posted this, it was over…