tests/testthat/test_classif_geoDA.R

context("classif_geoDA")

test_that("classif_geoDA", {
  requirePackagesOrSkip("DiscriMiner", default.method = "load")

  set.seed(getOption("mlr.debug.seed"))
  m = DiscriMiner::geoDA(multiclass.train[, -multiclass.class.col], group = multiclass.train[, multiclass.class.col])
  p =  DiscriMiner::classify(m, newdata = multiclass.test[, -multiclass.class.col])
  testSimple("classif.geoDA", multiclass.df, multiclass.target, multiclass.train.inds, p$pred_class)

  tt = function(formula, data, subset, ...) {
    j = which(colnames(data) == as.character(formula)[2])
    m = DiscriMiner::geoDA(variables = data[subset, -j], group = data[subset, j])
    list(model = m, target = j)
  }

  tp = function(model, newdata) {
    DiscriMiner::classify(model$model, newdata = newdata[, -model$target])$pred_class
  }

  testCV("classif.geoDA", multiclass.df, multiclass.target, tune.train = tt, tune.predict = tp)
})
guillermozbta/mir documentation built on May 11, 2019, 6:27 p.m.