Fig. 5

R-squared values (bottom) and selected features (top) in Support Vector Regression model using a polynomial kernel. Only cases showing positive R-squared values (larger than 0) were presented, and the cases were sorted on the performance. The right figure presents the counts, that is, the number of selections per feature.