Nothing
test_that("global_validation correctly handles missing predictions", {
skip_if_not_installed("randomForest")
data("iris")
set.seed(123)
ctrl <- caret::trainControl(method="cv")
model <- caret::train(iris[,c("Sepal.Width", "Petal.Length", "Petal.Width")],
iris[,c("Sepal.Length")],
method="rf", trControl=ctrl, ntree=10)
expect_error(global_validation(model))
})
test_that("global_validation works with caret regression", {
skip_if_not_installed("randomForest")
data("iris")
set.seed(123)
ctrl <- caret::trainControl(method="cv", savePredictions="final")
model <- caret::train(iris[,c("Sepal.Width", "Petal.Length", "Petal.Width")],
iris[,c("Sepal.Length")],
method="rf", trControl=ctrl, ntree=10)
expect_equal(global_validation(model),
c("RMSE"=0.3307870, "Rsquared"=0.8400544, "MAE"=0.2621827),
tolerance = 0.02)
})
test_that("global_validation works with caret classification", {
skip_if_not_installed("randomForest")
data("iris")
set.seed(123)
ctrl <- caret::trainControl(method="cv", savePredictions="final")
model <- caret::train(iris[,c("Sepal.Width", "Petal.Length", "Petal.Width", "Sepal.Length")],
iris[,c("Species")],
method="rf", trControl=ctrl, ntree=10)
expect_equal(global_validation(model)[1:2],
c("Accuracy"=0.96, "Kappa"=0.94),
tolerance = 0.02)
})
test_that("global_validation works with CreateSpacetimeFolds", {
skip_if_not_installed("randomForest")
data("iris")
set.seed(123)
iris$folds <- sample(rep(1:10, ceiling(nrow(iris)/10)), nrow(iris))
indices <- CreateSpacetimeFolds(iris, "folds")
ctrl <- caret::trainControl(method="cv", savePredictions="final", index = indices$index)
model <- caret::train(iris[,c("Sepal.Width", "Petal.Length", "Petal.Width", "Sepal.Length")],
iris[,c("Species")],
method="rf", trControl=ctrl, ntree=10)
expect_equal(global_validation(model)[1:2],
c("Accuracy"=0.96, "Kappa"=0.94),
tolerance = 0.02)
})
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