default values for increasing models and samples after classification fails
Arash and I are wondering why the default value of increasing the number of samples are that large (+50). Especially when you use regular sampling the increase of just one sample leads to different samples and the computation time is increased a lot!
Besides the "increase number" of models is just 15 which does not lead to more models after the classification in my experience.
I usually use more then 30 models in one resampling step.
Are we missing something here? What were the intentions, when those numbers were established?