msgl (version 2.0.125.0)

msgl.algorithm.config: Create a new algorithm configuration

Description

With the exception of verbose it is not recommended to change any of the default values.

Usage

msgl.algorithm.config(tolerance_penalized_main_equation_loop = 1e-10,
    tolerance_penalized_inner_loop_alpha = 1e-04,
    tolerance_penalized_inner_loop_beta = 1,
    tolerance_penalized_middel_loop_alpha = 0.01,
    tolerance_penalized_outer_loop_alpha = 0.01,
    tolerance_penalized_outer_loop_beta = 0,
    tolerance_penalized_outer_loop_gamma = 1e-05,
    use_bound_optimization = TRUE,
    use_stepsize_optimization_in_penalizeed_loop = TRUE,
    stepsize_opt_penalized_initial_t = 1,
    stepsize_opt_penalized_a = 0.1,
    stepsize_opt_penalized_b = 0.1, verbose = TRUE)

Arguments

tolerance_penalized_main_equation_loop

tolerance threshold.

tolerance_penalized_inner_loop_alpha

tolerance threshold.

tolerance_penalized_inner_loop_beta

tolerance threshold.

tolerance_penalized_middel_loop_alpha

tolerance threshold.

tolerance_penalized_outer_loop_alpha

tolerance threshold.

tolerance_penalized_outer_loop_beta

tolerance threshold.

tolerance_penalized_outer_loop_gamma

tolerance threshold.

use_bound_optimization

if TRUE hessian bound check will be used.

use_stepsize_optimization_in_penalizeed_loop

if TRUE step-size optimization will be used.

stepsize_opt_penalized_initial_t

initial step-size.

stepsize_opt_penalized_a

step-size optimization parameter.

stepsize_opt_penalized_b

step-size optimization parameter.

verbose

If TRUE some information, regarding the status of the algorithm, will be printed in the R terminal.

Value

• A configuration.

Examples

data(SimData)
x <- sim.data$x
classes <- sim.data$classes

# Create configuration
config <- msgl.algorithm.config(verbose = FALSE)

lambda <- msgl.lambda.seq(x, classes, alpha = .5, d = 50,
 lambda.min = 0.05, algorithm.config = config)

fit <- msgl(x, classes, alpha = .5, lambda = lambda,
 algorithm.config = config)