PLS variable importance

[jmh579]

Implement partial least squares variable importance in addition to random forest variable importance

[jmh579]

caret varImp documentation:

"Partial Least Squares: the variable importance measure here is based on weighted sums of the absolute regression coefficients. The weights are a function of the reduction of the sums of squares across the number of PLS components and are computed separately for each outcome. Therefore, the contribution of the coefficients are weighted proportionally to the reduction in the sums of squares."

Example:
gbmImp <- varImp(gbmFit3, scale = FALSE)
where gbmFit3 is a trained model

[jmh579]

Addressed in 0.2.0