Line search fails in training ksvm prob.model

Question

Following up from Invalid probability model for large support vector machines using ksvm in R:

I am training an SVM using ksvm from the kernlab package in R. I want

Answer 1

I do not understand the behavior of the optimizer. if max iteration is reached, no problem. but if step is lower than min_step it calls .SigmoidPredict which does not return A and B. I do not think that the solution is to decrease min_step, but not to call .SigmoidPredict, so I commented it out. btw, I do not understand why they do not use glm to estimate A and B.

here's a repository based on the latest source from cran with the call to SigmoidPredict commented out.

devtools::install_github('elad663/kernlab')