Granular Weighted Binning by Generalized Boosted Model

May 7, 2019

(This article was first published on S+/R – Yet Another Blog in Statistical Computing, and kindly contributed to R-bloggers)

In the post, I’ve shown how to do the weighted binning with the function wqtl_bin() by the iterative partitioning. However, the outcome from wqtl_bin() sometimes can be too coarse. The function wgbm_bin() ( leverages the idea of gbm() that implements the Generalized Boosted Model and generates more granular weighted binning outcomes.

Below is the demonstration showing the difference between wqtl_bin() and wgbm_bin() outcomes. Even with the same data, the wgbm_bin() function is able to generate a more granular binning result and 14% higher Information Value.


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