Modules

Regression and classification:

• RLS - regularized least-squares regression
• LeaveOneOutRLS - RLS with leave-one-out regularization parameter selection
• KFoldRLS - RLS with Kfold cross-validation regularization parameter selection
• LeavePairOutRLS - RLS with leave-pair-out regularization parameter selection
• CGRLS - linear conjugate gradient RLS

Learning to rank:

• GlobalRankRLS - ranking regularized least-squares, ordinal regression
• QueryRankRLS - ranking regularized least-squares, query-structured data
• PPRankRLS - ranking regularized least-squares, pairwise preferences
• LeavePairOutRankRLS - GlobalRankRLS with leave-pair-out regularization parameter selection
• KfoldRankRLS - GlobalRankRLS with Kfold cross-validation regularization parameter selection
• LeaveQueryOutRankRLS - QueryRankRLS with leave-query-out regularization parameter selection
• CGRankRLS - linear conjugate gradient RankRLS
• PCGRankRLS - linear conjugate gradient RankRLS with pairwise preferences

Feature selection:

• GreedyRLS - greedy regularized least-squares feature selection

Paired inputs, Kronecker kernels, zero-shot learning:

• KronRLS - Kronecker kernel RLS for pairwise data with complete training set
• CGKronRLS - Kronecker kernel RLS for pairwise data with incomplete (sparse) training set
• TwoStepRLS - Two step training method with RLS for pairwise data with complete training set

Clustering:

• MMC - unsupervised RLS; maximum margin clustering type, stochastic search
• SteepestDescentMMC - unsupervised RLS; maximum margin clustering type, steepest descent
• InteractiveRlsClassifier - interactive RLS clustering

Kernels:

• LinearKernel
• GaussianKernel
• PolynomialKernel

Performance measures:

• accuracy - Binary classification accuracy
• auc - Area under ROC curve
• cindex - Concordance index (pairwise ranking accuracy)
• fscore - F1-score
• ova_accuracy - one-vs-all multiclass accuracy
• spearman - Spearman rank correlation
• sqmprank - squared magniture preserving ranking error
• sqerror - mean squared error

Predictors:

• LinearPredictor
• KernelPredictor
• LinearPairwisePredictor
• KernelPairwisePredictor