A Swiss Army Knife for Machine Learning Practice, cross validation, model selection, ensemble selection, stacking. It is built based on scikit-learn package.
Cross validation
Feature Engineering
Hyper parameter optimization, generate hundreds of models using different model parameters
Ensemble Selection, forward stepwise greedy ensemble with replacement
Model Stacking, Raw feature + meta feature, XGBoost + AdaBoost
All parameters
PS: need to modify gen_featu.py when apply a new task