weight_control {deepregression}

Options for weights of layers

Description

Options for weights of layers

Usage

weight_control(
  specific_weight_options = NULL,
  general_weight_options = list(activation = NULL, use_bias = FALSE, trainable = TRUE,
    kernel_initializer = "glorot_uniform", bias_initializer = "zeros", kernel_regularizer
    = NULL, bias_regularizer = NULL, activity_regularizer = NULL, kernel_constraint =
    NULL, bias_constraint = NULL),
  warmstart_weights = NULL,
  shared_layers = NULL
)

Arguments

specific_weight_options

specific options for certain weight terms; must be a list of length length(list_of_formulas) and each element in turn a named list (names are term names as in the formula) with specific options in a list

general_weight_options

default options for layers

warmstart_weights

While all keras layer options are availabe, the user can further specify a list for each distribution parameter with list elements corresponding to term names with values as vectors corresponding to start weights of the respective weights

shared_layers

list for each distribution parameter; each list item can be again a list of character vectors specifying terms which share layers

Value

Returns a list with options