A major criticism on the binning algorithm as well as on the WoE transformation is that the use of binned predictors will decrease the model predictive power due to the...continue reading.
In the post https://statcompute.wordpress.com/2019/10/13/assess-variable-importance-in-grnn, it was shown how to assess the variable importance of a GRNN by the decrease in GoF statistics, e.g. AUC, after averaging or dropping the variable...continue reading.
The function grnn.margin() (https://github.com/statcompute/yager/blob/master/code/grnn.margin.R) was my first attempt to explore the relationship between each predictor and the response in a General Regression Neural Network, which usually is considered the Black-Box...continue reading.
A major advantage of General Regression Neural Networks (GRNN) over other types of neural networks is that there is only a single hyper-parameter, namely the sigma. In the previous post...continue reading.
In the post (https://statcompute.wordpress.com/2019/07/14/yet-another-r-package-for-general-regression-neural-network), several advantages of General Regression Neural Network (GRNN) have been discussed. However, as pointed out by Specht, a major weakness of GRNN is the high computational...continue reading.
Compared with other types of neural networks, General Regression Neural Network (Specht, 1991) is advantageous in several aspects. Being an universal approximation function, GRNN has only one tuning parameter to...continue reading.
In my previous post https://statcompute.wordpress.com/2019/02/03/sobol-sequence-vs-uniform-random-in-hyper-parameter-optimization/, I’ve shown the difference between the uniform pseudo random and the quasi random number generators in the hyper-parameter optimization of machine learning. Latin Hypercube Sampling...continue reading.
In the intro section of my MOB package (https://github.com/statcompute/MonotonicBinning#introduction), reasons and benefits of using WoE transformations in the context of logistic regressions with binary outcomes had been discussed. What’s more,...continue reading.
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.