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bmrm
View on CRAN: Click
here
Download and install bmrm package within the R console
Install from CRAN:
install.packages("bmrm")
Install from Github:
library("remotes")
install_github("cran/bmrm")
Install by package version:
library("remotes")
install_version("bmrm", "4.1")
Attach the package and use:
library("bmrm")
Maintained by
Julien Prados
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-05-14
Latest Update: 2023-04-14
Description:
Bundle methods for minimization of convex and non-convex risk
under L1 or L2 regularization. Implements the algorithm proposed by Teo et
al. (JMLR 2010) as well as the extension proposed by Do and Artieres (JMLR
2012). The package comes with lot of loss functions for machine learning
which make it powerful for big data analysis. The applications includes:
structured prediction, linear SVM, multi-class SVM, f-beta optimization,
ROC optimization, ordinal regression, quantile regression,
epsilon insensitive regression, least mean square, logistic regression,
least absolute deviation regression (see package examples), etc... all with
L1 and L2 regularization.
How to cite:
Julien Prados (2013). bmrm: Bundle Methods for Regularized Risk Minimization Package. R package version 4.1, https://cran.r-project.org/web/packages/bmrm. Accessed 21 Dec. 2024.
Previous versions and publish date:
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Other R packages that bmrm depends,
imports, suggests or enhances
Functions, R codes and Examples using
the bmrm R package
Some associated functions: balanced.cv.fold . balanced.loss.weights . bhattacharyya.coefficient . binaryClassificationLoss . costMatrix . gradient . hclust_fca . hellinger.dist . is.convex . iterative.hclust . linearRegressionLoss . lpSVM . lvalue . mmc . mmcLoss . multivariateHingeLoss . nrbm . ontologyLoss . ordinalRegressionLoss . predict.mmc . preferenceLoss . print.roc.stat . rank.linear.weights . roc.stat . rowmean . softMarginVectorLoss . softmaxLoss . wolfe.linesearch .
Some associated R codes: RcppExports.R . loss_convex.R . loss_core.R . loss_non_convex.R . misc.R . ml_misc.R . mmc.R . nrbm.R . svmLP.R . wolfe.R . Full bmrm package functions and examples
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