sgl.standard.config

<code>sgl.standard.config &lt;- sgl.algorithm.config()</code>

datasets

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. Armadillo is licensed under the MPL 2.0. The
        Armadillo C++ library is primarily developed at NICTA
        (Australia) by Conrad Sanderson, with contributions from around
        the world. Furthermore the package utilize various Boost
        libraries, in particular the Tuple library by Jaakko Jarvi and
        the Random library by Jens Maurer. The Boost libraries are
        licensed under the Boost Software License.

Martin Vincent

msgl

High dimensional multiclass classification using sparse group
        lasso

sgl.standard.config function

List of 13
 $ tolerance_penalized_main_equation_loop      : num 1e-10
 $ tolerance_penalized_inner_loop_alpha        : num 1e-04
 $ tolerance_penalized_inner_loop_beta         : num 1
 $ tolerance_penalized_middel_loop_alpha       : num 0.01
 $ tolerance_penalized_outer_loop_alpha        : num 0.01
 $ tolerance_penalized_outer_loop_beta         : num 0
 $ tolerance_penalized_outer_loop_gamma        : num 1e-05
 $ use_bound_optimization                      : logi TRUE
 $ use_stepsize_optimization_in_penalizeed_loop: logi TRUE
 $ stepsize_opt_penalized_initial_t            : num 1
 $ stepsize_opt_penalized_a                    : num 0.1
 $ stepsize_opt_penalized_b                    : num 0.1
 $ verbose                                     : logi FALSE

sgl.standard.config: Standard algorithm configuration

Description

Usage

Arguments

format