Nothing
## Trained Models
test_that("grid tuning of models", {
skip_if_not(TEST_TRAINING)
with_parallel({
models <- c(
"AdaBagModel",
"AdaBoostModel",
"BARTMachineModel",
"BlackBoostModel",
"C50Model",
"CForestModel",
"EarthModel",
"FDAModel",
"GAMBoostModel",
"GBMModel",
"GLMBoostModel",
"GLMNetModel",
"KNNModel",
"LDAModel",
"MDAModel",
"NNetModel",
"PLSModel",
"RandomForestModel",
"RangerModel",
"RFSRCModel",
"RPartModel",
"SVMANOVAModel",
"SVMBesselModel",
"SVMLaplaceModel",
"SVMLinearModel",
"SVMPolyModel",
"SVMRadialModel",
"SVMTanhModel",
"XGBDARTModel",
"XGBLinearModel",
"XGBTreeModel"
)
control <- CVControl(folds = 3)
test_tune_grid1 <- function(model) {
fit(type ~ ., data = Pima.tr,
model = TunedModel(model, grid = 1, control = control))
}
test_tune_grid2 <- function(model) {
fit(type ~ ., data = Pima.tr,
model = TunedModel(model, grid = 3, control = control))
}
test_tune_grid3 <- function(model) {
fit(type ~ ., data = Pima.tr,
model = TunedModel(model, grid = TuningGrid(size = 100, random = 10),
control = control))
}
for (model in models) {
expect_is(test_tune_grid1(model), "MLModelFit")
expect_is(test_tune_grid2(model), "MLModelFit")
expect_is(test_tune_grid3(model), "MLModelFit")
}
})
})
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