CRAN - Package msgl (Version:2.0.125.0): High dimensional multiclass classification using sparse group lasso

Publikation: Bidrag der ikke har en tekstform › Softwareprogram › Forskning

Standard

CRAN - Package msgl (Version:2.0.125.0) : High dimensional multiclass classification using sparse group lasso . Vincent, Martin (Producent). 2014.

Publikation: Bidrag der ikke har en tekstform › Softwareprogram › Forskning

Harvard

Vincent, M, CRAN - Package msgl (Version:2.0.125.0): High dimensional multiclass classification using sparse group lasso , 2014, Softwareprogram. <http://cran.r-project.org/web/packages/msgl/index.html>

APA

Vincent, M. (Producent). (2014). CRAN - Package msgl (Version:2.0.125.0): High dimensional multiclass classification using sparse group lasso . Softwareprogram http://cran.r-project.org/web/packages/msgl/index.html

Vancouver

Vincent M (Producent). CRAN - Package msgl (Version:2.0.125.0): High dimensional multiclass classification using sparse group lasso 2014.

Author

Vincent, Martin (Producent). / CRAN - Package msgl (Version:2.0.125.0) : High dimensional multiclass classification using sparse group lasso . [Softwareprogram].

Bibtex

@misc{4c7be73fd7a24e36930a3c39f8d187e2,
title = "CRAN - Package msgl (Version:2.0.125.0): High dimensional multiclass classification using sparse group lasso ",
abstract = "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.",
author = "Martin Vincent",
year = "2014",
language = "English",

}

RIS

TY - COMP

T1 - CRAN - Package msgl (Version:2.0.125.0)

T2 - High dimensional multiclass classification using sparse group lasso

A2 - Vincent, Martin

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

M3 - Computer programme

ER -

ID: 94754977