3 papers
cs.LG2020
How to tune the RBF SVM hyperparameters?: An empirical evaluation of 18 search algorithms
Jacques Wainer, Pablo Fonseca
SVM with an RBF kernel is usually one of the best classification algorithms for most data sets, but it is important to tune the two hyperparameters and to the data itself.…
cs.LG2018
Nested cross-validation when selecting classifiers is overzealous for most practical applications
Jacques Wainer, Gavin Cawley
When selecting a classification algorithm to be applied to a particular problem, one has to simultaneously select the best algorithm for that dataset \emph{and} the best set of hyp…
cs.LG2016
Comparison of 14 different families of classification algorithms on 115 binary datasets
Jacques Wainer
We tested 14 very different classification algorithms (random forest, gradient boosting machines, SVM - linear, polynomial, and RBF - 1-hidden-layer neural nets, extreme learning m…