tests/testthat/test_classif_dbnDNN.R

In guillermozbta/mir: Machine Learning in R

context("classif_dbnDNN")

test_that("classif_dbnDNN", {
  requirePackagesOrSkip("deepnet", default.method = "load")

  parset.list1 = list(
    list(output = "softmax"),
    list(output = "softmax", hidden = 7)
  )

  parset.list2 = list(
    list(),
    list(hidden = 7)
  )

  old.predicts.list = list()

  for (i in seq_along(parset.list1)) {
    parset = parset.list1[[i]]


    set.seed(getOption("mlr.debug.seed"))
   capture.output({
    # neuralnet is not dealing with formula with `.` well
    x = data.matrix(binaryclass.train[, -ncol(binaryclass.train)])
    y = binaryclass.train[, ncol(binaryclass.train)]

    dict = sort(unique(y))
    onehot = matrix(0, length(y), length(dict))
    for (j in seq_along(dict)) {
      ind = which(y == dict[j])
      onehot[ind, j] = 1
    }
    pars = list(x = x, y = onehot)
    pars = c(pars, parset)
    m = do.call(deepnet::dbn.dnn.train, pars)
    p = deepnet::nn.predict(m, data.matrix(binaryclass.test[, -ncol(binaryclass.test)]))
    colnames(p) = binaryclass.class.levs
    old.predicts.list[[i]] = as.factor(colnames(p)[max.col(p)])
  })
}

  testSimpleParsets("classif.dbnDNN", binaryclass.df, binaryclass.target,
    binaryclass.train.inds, old.predicts.list, parset.list2)
})