API for bmrm
Bundle Methods for Regularized Risk Minimization Package
| Global functions | |
|---|---|
| balanced.cv.fold | Man page |
| balanced.loss.weights | Man page |
| bhattacharyya.coefficient | Man page |
| binaryClassificationLoss | Man page |
| costMatrix | Man page |
| epsilonInsensitiveRegressionLoss | Man page |
| fbetaLoss | Man page |
| gradient | Man page |
| gradient.default | Man page |
| gradient<- | Man page |
| gradient<-.default | Man page |
| hclust_fca | Man page |
| hellinger.dist | Man page |
| hingeLoss | Man page |
| is.convex | Man page |
| is.convex.default | Man page |
| is.convex<- | Man page |
| is.convex<-.default | Man page |
| iterative.hclust | Man page |
| ladRegressionLoss | Man page |
| linearRegressionLoss | Man page |
| lmsRegressionLoss | Man page |
| logisticLoss | Man page |
| lpSVM | Man page |
| lvalue | Man page |
| lvalue.default | Man page |
| lvalue<- | Man page |
| lvalue<-.default | Man page |
| mmc | Man page |
| mmcLoss | Man page |
| multivariateHingeLoss | Man page |
| nrbm | Man page |
| nrbmL1 | Man page |
| ontologyLoss | Man page |
| ordinalRegressionLoss | Man page |
| predict.mmc | Man page |
| predict.svmLP | Man page |
| predict.svmMLP | Man page |
| preferenceLoss | Man page |
| print.roc.stat | Man page |
| quantileRegressionLoss | Man page |
| rank.linear.weights | Man page |
| roc.stat | Man page |
| rocLoss | Man page |
| rowmean | Man page |
| softMarginVectorLoss | Man page |
| softmaxLoss | Man page |
| svmLP | Man page |
| svmMulticlassLP | Man page |
| wolfe.linesearch | Man page |
