tests/testthat/test-deep_neural_network.R

In easyml: Easily Build and Evaluate Machine Learning Models

library(easyml)
context("deep_neural_network")

library(darch)
test_that("Test easy_deep_neural_network.", {
  # Load data
  data("cocaine_dependence", package = "easyml")
  data("prostate", package = "easyml")
  
  # Settings
  .n_samples <- 5
  .n_divisions <- 5
  .n_iterations <- 2
  .n_core <- 1
  
  # Test binomial
  results <- easy_deep_neural_network(cocaine_dependence, "diagnosis",
                                      family = "binomial", preprocess = preprocess_scale,
                                      exclude_variables = c("subject"),
                                      categorical_variables = c("male"),
                                      n_samples = .n_samples, n_divisions = .n_divisions,
                                      n_iterations = .n_iterations, random_state = 12345, n_core = .n_core)
  expect_equal(class(results), "easy_deep_neural_network")
  
  # Test gaussian
  results <- easy_deep_neural_network(prostate, "lpsa", 
                                      preprocess = preprocess_scale, 
                                      n_samples = .n_samples, n_divisions = .n_divisions, 
                                      n_iterations = .n_iterations, random_state = 12345, n_core = .n_core)
  expect_equal(class(results), "easy_deep_neural_network")
})