In the post https://statcompute.wordpress.com/2019/04/27/more-general-weighted-binning, 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....continue reading.
In my GitHub repository (https://github.com/statcompute/MonotonicBinning), multiple R functions have been developed to implement the monotonic binning by using either iterative discretization or isotonic regression. With these functions, we can run...continue reading.
In addition to monotonic binning algorithms introduced in my previous post (https://statcompute.wordpress.com/2019/03/10/a-summary-of-my-home-brew-binning-algorithms-for-scorecard-development), two more functions based on Generalized Boosted Regression Models have been added to my GitHub repository, gbm_bin() and...continue reading.
In my previous post (https://statcompute.wordpress.com/2019/03/10/a-summary-of-my-home-brew-binning-algorithms-for-scorecard-development), I’ve shown different monotonic binning algorithm that I developed over time. However, these binning functions are all useless without a deployment vehicle in production. During...continue reading.
Thus far, I have published four different monotonic binning algorithms for the scorecard development and think that it might be a right timing to do a quick summary. R functions...continue reading.
In the previous post (https://statcompute.wordpress.com/2019/02/03/sobol-sequence-vs-uniform-random-in-hyper-parameter-optimization), it is shown how to identify the optimal hyper-parameter in a General Regression Neural Network by using the Sobol sequence and the uniform random generator...continue reading.
Tuning hyper-parameters might be the most tedious yet crucial in various machine learning algorithms, such as neural networks, svm, or boosting. The configuration of hyper-parameters not only impacts the computational...continue reading.
In the post (https://statcompute.wordpress.com/2018/11/23/more-robust-monotonic-binning-based-on-isotonic-regression), a more robust version of monotonic binning based on the isotonic regression was introduced. Nonetheless, due to the loss of granularity, the predictability has been somewhat...continue reading.
Since publishing the monotonic binning function based upon the isotonic regression (https://statcompute.wordpress.com/2017/06/15/finer-monotonic-binning-based-on-isotonic-regression), I’ve received some feedback from peers. A potential concern is that, albeit improving the granularity and predictability, the...continue reading.