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library(caret)
test_that('train classification', {
skip_on_cran()
set.seed(1)
tr_dat <- twoClassSim(200)
te_dat <- twoClassSim(200)
set.seed(2)
class_trim <- train(Class ~ ., data = tr_dat,
method = "rpart",
tuneGrid = data.frame(cp = 0.22),
preProc = c("center", "bagImpute"),
trControl = trainControl(method = "none",
classProbs = TRUE,
trim = TRUE))
class_trim <- caret:::trim.train(class_trim)
set.seed(2)
class_notrim <- train(Class ~ ., data = tr_dat,
method = "rpart",
tuneGrid = data.frame(cp = 0.22),
preProc = c("center", "bagImpute"),
trControl = trainControl(method = "none",
classProbs = TRUE,
trim = FALSE))
expect_equal(predict(class_trim, te_dat),
predict(class_notrim, te_dat))
expect_equal(predict(class_trim, te_dat, type = "prob"),
predict(class_notrim, te_dat, type = "prob"))
expect_less_than(object.size(class_trim)-object.size(class_notrim), 0)
})
test_that('train regression', {
skip_on_cran()
set.seed(1)
tr_dat <- SLC14_1(200)
te_dat <- SLC14_1(200)
set.seed(2)
reg_trim <- train(y ~ ., data = tr_dat,
method = "rpart",
tuneGrid = data.frame(cp = 0.12),
trControl = trainControl(method = "none",
trim = TRUE))
reg_trim <- caret:::trim.train(reg_trim)
set.seed(2)
reg_notrim <- train(y ~ ., data = tr_dat,
method = "rpart",
tuneGrid = data.frame(cp = 0.12),
trControl = trainControl(method = "none",
trim = FALSE))
expect_equal(predict(reg_trim, te_dat),
predict(reg_notrim, te_dat))
expect_less_than(object.size(reg_trim)-object.size(reg_notrim), 0)
})
test_that('train/earth classification', {
skip_on_cran()
set.seed(1)
tr_dat <- twoClassSim(200)
te_dat <- twoClassSim(200)
set.seed(2)
class_trim <- train(Class ~ ., data = tr_dat,
method = "earth",
tuneGrid = data.frame(nprune = 3, degree = 1),
trControl = trainControl(method = "none",
classProbs = TRUE,
trim = TRUE))
class_trim <- caret:::trim.train(class_trim)
set.seed(2)
class_notrim <- train(Class ~ ., data = tr_dat,
method = "earth",
tuneGrid = data.frame(nprune = 3, degree = 1),
trControl = trainControl(method = "none",
classProbs = TRUE,
trim = FALSE))
expect_equal(predict(class_trim, te_dat),
predict(class_notrim, te_dat))
expect_equal(predict(class_trim, te_dat, type = "prob"),
predict(class_notrim, te_dat, type = "prob"))
expect_less_than(object.size(class_trim)-object.size(class_notrim), 0)
})
test_that('train/earth regression', {
skip_on_cran()
set.seed(1)
tr_dat <- SLC14_1(200)
te_dat <- SLC14_1(200)
set.seed(2)
reg_trim <- train(y ~ ., data = tr_dat,
method = "earth",
tuneGrid = data.frame(nprune = 3, degree = 1),
trControl = trainControl(method = "none",
trim = TRUE))
set.seed(2)
reg_notrim <- train(y ~ ., data = tr_dat,
method = "earth",
tuneGrid = data.frame(nprune = 3, degree = 1),
trControl = trainControl(method = "none",
trim = FALSE))
expect_equal(predict(reg_trim, te_dat),
predict(reg_notrim, te_dat))
expect_less_than(object.size(reg_trim)-object.size(reg_notrim), 0)
})
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