msgl: High Dimensional Multiclass Classification Using Sparse Group Lasso

Multinomial logistic regression with sparse group lasso penalty. Simultaneous feature selection and parameter estimation for classification. Suitable for high dimensional multiclass classification with many classes. The algorithm computes the sparse group lasso penalized maximum likelihood estimate. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.

AuthorMartin Vincent
Date of publication2016-12-29 01:09:04
MaintainerMartin Vincent <martin.vincent.dk@gmail.com>
LicenseGPL (>= 2)
Version2.3.5
http://dx.doi.org/10.1016/j.csda.2013.06.004, https://github.com/vincent- dk/msgl

View on CRAN

Functions

best_model.msgl Man page
classes Man page
coef.msgl Man page
cv Man page
Err.msgl Man page
features.msgl Man page
features_stat.msgl Man page
fit Man page
lambda Man page
models.msgl Man page
msgl Man page
msgl.algorithm.config Man page
msgl.c.config Man page
msgl.cv Man page
msgl.lambda.seq Man page
msgl-package Man page
msgl.standard.config Man page
msgl.subsampling Man page
nmod.msgl Man page
parameters.msgl Man page
parameters_stat.msgl Man page
predict.msgl Man page
PrimaryCancers Man page
print.msgl Man page
SimData Man page
subsampling Man page
x Man page

Files

msgl
msgl/inst
msgl/inst/CITATION
msgl/inst/NEWS.Rd
msgl/inst/doc
msgl/inst/doc/quick-start.html
msgl/inst/doc/quick-start.R
msgl/inst/doc/quick-start.Rmd
msgl/tests
msgl/tests/msgl_grouping_test_3.R
msgl/tests/msgl_test_1.R
msgl/tests/msgl_grouping_test_1.R
msgl/tests/msgl_test_3.R
msgl/tests/msgl_test_4.R
msgl/tests/msgl_cv_test_1.R
msgl/tests/msgl_grouping_test_2.R
msgl/tests/msgl_grouping_test_4.R
msgl/tests/msgl_cv_test_3.R
msgl/tests/msgl_configuration_test.R
msgl/tests/msgl_predict_test_1.R
msgl/tests/msgl_predict_test_2.R
msgl/tests/msgl_cv_test_4.R
msgl/tests/msgl_sub_test_1.R
msgl/tests/msgl_test_2.R
msgl/tests/msgl_cv_test_2.R
msgl/src
msgl/src/Makevars
msgl/src/msgl.cpp
msgl/src/multinomial_response.h
msgl/src/multinomial_loss.h
msgl/src/pkg_c_config.h
msgl/NAMESPACE
msgl/data
msgl/data/PrimaryCancers.RData
msgl/data/SimData.RData
msgl/R
msgl/R/cv.R msgl/R/subsampling.R msgl/R/predict.R msgl/R/lambda.R msgl/R/navigate.R msgl/R/fit.R msgl/R/startup.R msgl/R/msgl.R msgl/R/config.R msgl/R/process-arguments.R
msgl/vignettes
msgl/vignettes/quick-start.Rmd
msgl/MD5
msgl/build
msgl/build/vignette.rds
msgl/DESCRIPTION
msgl/man
msgl/man/classes.Rd msgl/man/msgl.standard.config.Rd msgl/man/fit.Rd msgl/man/SimData.Rd msgl/man/x.Rd msgl/man/features.msgl.Rd msgl/man/cv.Rd msgl/man/msgl.subsampling.Rd msgl/man/print.msgl.Rd msgl/man/coef.msgl.Rd msgl/man/msgl-package.Rd msgl/man/msgl.c.config.Rd msgl/man/best_model.msgl.Rd msgl/man/PrimaryCancers.Rd msgl/man/predict.msgl.Rd msgl/man/models.msgl.Rd msgl/man/Err.msgl.Rd msgl/man/lambda.Rd msgl/man/msgl.Rd msgl/man/parameters.msgl.Rd msgl/man/msgl.cv.Rd msgl/man/features_stat.msgl.Rd msgl/man/msgl.lambda.seq.Rd msgl/man/parameters_stat.msgl.Rd msgl/man/msgl.algorithm.config.Rd msgl/man/nmod.msgl.Rd msgl/man/subsampling.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

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