Prediction-weighted partial least-squares regression method (PWPLS)

Prediction-weighted partial least-squares (PWPLS) is a progressive approach of partial least-squares (PLS) regression. PWPLS is a simple, efficient, and evolutionary algorithm to select appropriate predictor variables, and weight each selected predictor variable for improving predictability when there is only one dependent variable. We applied PWPLS to two QSAR data sets, and compared the predictability results of PWPLS with that of PLS.