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msgl (version 0.1.7)

High dimensional multiclass classification using sparse group lasso

Description

Sparse group lasso multiclass classification, suitable for high dimensional problems with many classes. Fast algorithm for solving the multinomial sparse group lasso convex optimization problem. This package apply template metaprogramming techniques, therefore -- when compiling the package from source -- a high level of optimization is needed to gain full speed (e.g. for the GCC compiler use -O3). Use of multiple processors for cross validation and subsampling is supported through OpenMP. The Armadillo C++ library is used as the primary linear algebra engine.

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Version

Install

install.packages('msgl')

Monthly Downloads

154

Version

0.1.7

License

GPL (>= 2)

Maintainer

Martin Vincent

Last Published

February 19th, 2014

Functions in msgl (0.1.7)

msgl.cv

Multinomial sparse group lasso cross validation using multiple possessors
predict.msgl

Predict
msgl.lambda.seq

Computes a lambda sequence for the regularization path
sgl.standard.config

Standard algorithm configuration
sim.data

Simulated data set
sgl.algorithm.config

Create a new algorithm configuration
msgl.subsampling

Multinomial sparse group lasso generic subsampling procedure
msgl

Fit a multinomial sparse group lasso regularization path.