Man pages for bmrm
Bundle Methods for Regularized Risk Minimization Package
| balanced.cv.fold | Split a dataset for Cross Validation taking into account... |
| balanced.loss.weights | Compute loss.weights so that total losses of each class is... |
| bhattacharyya.coefficient | Compute Bhattacharyya coefficient needed for Hellinger... |
| binaryClassificationLoss | Loss functions for binary classification |
| costMatrix | Compute or check the structure of a cost matrix |
| gradient | Return or set gradient attribute |
| hclust_fca | Find first common ancestor of 2 nodes in an hclust object |
| hellinger.dist | Compute Hellinger distance |
| is.convex | Return or set is.convex attribute |
| iterative.hclust | Perform multiple hierachical clustering on random subsets of... |
| linearRegressionLoss | Loss functions to perform a regression |
| lpSVM | Linearly Programmed SVM |
| lvalue | Return or set lvalue attribute |
| mmc | Convenient wrapper function to solve max-margin clustering... |
| mmcLoss | Loss function for max-margin clustering |
| multivariateHingeLoss | The loss function for multivariate hinge loss |
| nrbm | Convex and non-convex risk minimization with L2... |
| ontologyLoss | Ontology Loss Function |
| ordinalRegressionLoss | The loss function for ordinal regression |
| predict.mmc | Predict class of new instances according to a mmc model |
| preferenceLoss | The loss function for Preference loss |
| print.roc.stat | Generic method overlad to print object of class roc.stat |
| rank.linear.weights | Rank linear weight of a linear model |
| roc.stat | Compute statistics for ROC curve plotting |
| rowmean | Columun means of a matrix based on a grouping variable |
| softMarginVectorLoss | Soft Margin Vector Loss function for multiclass SVM |
| softmaxLoss | softmax Loss Function |
| wolfe.linesearch | Wolfe Line Search |
