Probing for Sparse and Fast Variable Selection with Model-Based Boosting
Table 1
Total number of selected variables and intersection size for four variable selection techniques (boosting with 25-fold bootstrap, probing, stability selection, and the lasso with 10-fold cross-validation) on three gene expression data sets. The last column compares algorithm runtime in seconds.