circlus (version 0.0.2)

FLXMRspcauchy: Spherical Cauchy Driver for FlexMix Using Neural Networks

Description

This model driver for flexmix implements model-based clustering of spherical Cauchy distributions using neural networks in the M-step.

Usage

FLXMRspcauchy(
  formula = . ~ .,
  EPOCHS = 100,
  LR = 0.1,
  max_iter = 200,
  adam_iter = 5,
  free_iter = adam_iter,
  line_search_fn = "strong_wolfe"
)

Value

Returns an object of class FLXMC.

Arguments

formula

A formula.

EPOCHS

EPOCHS The number of epochs in the M-step estimation (default: 100).

LR

The learning rate used in the M-steo estimation (default: 0.1).

max_iter

The maximum number of iterations of the LBFGS optimizer (default: 200).

adam_iter

The number of iteration for which the adam optimizer is used before the algorithm switches to L-BFGS (default: 5).

free_iter

The number of initial iterations for which the model in M-step is fully reseted (default: adam_iter).

line_search_fn

The method used for line search in LBFGS (default: "strong_wolfe").

Examples

# \donttest{
if(torch::torch_is_installed()){
mix <- rbind(rpkb(30, 0.95, c(1, 0, 0)), rpkb(30, 0.9, c(-1, 0, 0)))
m1 <- flexmix::flexmix(mix ~ 1, k = 2, model = FLXMRspcauchy())
}
# }