API for bmrm
Bundle Methods for Regularized Risk Minimization Package

Global functions
balanced.cv.fold Man page Source code
binaryClassificationLoss Man page
costMatrix Man page Source code
epsilonInsensitiveRegressionLoss Man page Source code
fbetaLoss Man page Source code
gradient Man page Source code
gradient.default Man page Source code
gradient<- Man page Man page
gradient<-.default Man page
hclust.fca Man page Source code
hingeLoss Man page Source code
is.convex Man page Source code
is.convex.default Man page Source code
is.convex<- Man page Man page
is.convex<-.default Man page
iterative.hclust Man page Source code
ladRegressionLoss Man page Source code
linearRegressionLoss Man page
lmsRegressionLoss Man page Source code
logisticLoss Man page Source code
lpSVM Man page
lvalue Man page Source code
lvalue.default Man page Source code
lvalue<- Man page Man page
lvalue<-.default Man page
mmc Man page Source code
mmcLoss Man page Source code
nrbm Man page Man page Source code
nrbmL1 Man page Source code
ontologyLoss Man page Source code
ordinalRegressionLoss Man page Source code
predict.binaryClassificationLoss Source code
predict.linearRegressionLoss Source code
predict.logisticLoss Source code
predict.mmc Man page Source code
predict.ontologyLoss Source code
predict.ordinalRegressionLoss Source code
predict.rocLoss Source code
predict.softMarginVectorLoss Source code
predict.svmLP Man page Source code
predict.svmMLP Man page Source code
quantileRegressionLoss Man page Source code
roc.stat Man page Source code
rocLoss Man page Source code
set.convex Source code
softMarginVectorLoss Man page Source code
svmLP Man page Source code
svmMulticlassLP Man page Source code
tsvmLoss Man page Source code
wolfe.linesearch Man page Source code
bmrm documentation built on Feb. 19, 2018, 5:01 p.m.