creditmodel1.1.2

In this version I have:

Fixed some potential bugs in split_bins, ks_table_plot,ks_psi_plot,ks_value.
Add a new function pred_score for predicting new data using trained models.
Provide new functions perf_table,roc_plot,ks_plot,lift_plot,psi_plot for model validation drawings.

creditmodel1.1.1

In this version I have:

In this version I have:

Add a function data_exploration for data exploration.
Fixed some potential bugs in missing_proc, outliers_proc ,get_names
In lasso_filter, AUC&K-S is added to select the best lambda. In this way, not only can the set of variables that makes the AUC or K-S maximized be selected, but also the multicollinearity (which is difficult to eliminate by AIC in stepwise regression), can be minimized. That means instead of stepwise regression, the optimal combination of variables can be selected by lasso to solve the regression problem.
Visualize the number of variables, K-S or AUC values corresponding to different lambda.
Provide new functions``auc_value \ks_value`, which can calculate Kolmogorov-Smirnov (K-S) & AUC of multiple model results quickly.