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 |