| bmrm | Bundle Methods for Regularized Risk Minimization |
| costMatrix | Compute or check the structure of a cost matrix |
| epsilonInsensitiveRegressionLoss | The loss function to perform a epsilon-insensitive regression (Vapnik et al. 1997) |
| fbetaLoss | F beta score loss function |
| gradient | Return or set gradient attribute |
| gradient.default | Return or set gradient attribute |
| gradient<- | Return or set gradient attribute |
| gradient<-.default | Return or set gradient attribute |
| hingeLoss | Hinge Loss function for SVM |
| ladRegressionLoss | The loss function to perform a least absolute deviation regression |
| lmsRegressionLoss | The loss function to perform a least mean square regression |
| logisticRegressionLoss | The loss function to perform a logistic regression |
| nrbm | Convex and non-convex risk minimization with L2 regularization and limited memory |
| ordinalRegressionLoss | The loss function for ordinal regression |
| quantileRegressionLoss | The loss function to perform a quantile regression |
| rocLoss | The loss function to maximize area under the ROC curve |
| softMarginVectorLoss | Soft Margin Vector Loss function for multiclass SVM |