Regression

linearr Linear regression more routines
ridger Ridge regression
lassor LASSO
svmr Support vector regression
ksmoothr Kernel smoother
knnr k-nearest neighbor regression
pinvr Pseudo-inverse regression
plsr Partial least squares regression
plsm Partial least squares mapping
gpr Gaussian Process regression
testr Mean squared regression error
rsquared R^2-statistic

elements: datasets datafiles cells and doubles mappings classifiers mapping types.
operations: datasets datafiles cells and doubles mappings classifiers stacked parallel sequential dyadic.
user commands: datasets representation classifiers evaluation clustering examples support routines.
introductory examples: Introduction Scatterplots Datasets Datafiles Mappings Classifiers Evaluation Learning curves Feature curves Dimension reduction Combining classifiers Dissimilarities.
advanced examples.