engressionfit: Engression Fit Function

In engression: Engression Modelling

Engression Fit Function

Description

This function fits an Engression model to the provided data. It allows for the tuning of several parameters related to model complexity and training. The function is not meant to be exported but can be used within the package or for internal testing purposes.

Usage

engressionfit(
  X,
  Y,
  noise_dim = 100,
  hidden_dim = 100,
  num_layer = 3,
  dropout = 0.01,
  batch_norm = TRUE,
  num_epochs = 200,
  lr = 10^(-3),
  beta = 1,
  silent = FALSE
)

Arguments

X	A matrix or data frame representing the predictors.
Y	A matrix representing the target variable(s).
noise_dim	The dimension of the noise introduced in the model (default: 100).
hidden_dim	The size of the hidden layer in the model (default: 100).
num_layer	The number of layers in the model (default: 3).
dropout	The dropout rate to be used in the model in case no batch normalization is used (default: 0.01)
batch_norm	A boolean indicating whether to use batch-normalization (default: TRUE).
num_epochs	The number of epochs to be used in training (default: 200).
lr	The learning rate to be used in training (default: 10^-3).
beta	The beta scaling factor for energy loss (default: 1).
silent	A boolean indicating whether to suppress output during model training (default: FALSE).

Value

A list containing the trained engression model and a vector of loss values.

engression documentation built on Nov. 22, 2023, 9:06 a.m.