context("Validation Types")
# load the libraries
library(ModelComparison)
test_that("80/20 validation works", {
titanic <- PrepareNumericTitanic()
# create the models
comp <- GetModelComparisons(titanic[, -1], titanic[, 1], validation="80/20")
# predict the values for the dataset
pred.list <- predict(comp, titanic[, -1])
# check that there are the same number of predictions as there are models
expect_equal(length(comp$model.list), length(pred.list))
# ensure plot doesn't have any errors
plot(comp, titanic[, 1], titanic[, -1])
})
test_that("50/50 validation works", {
titanic <- PrepareNumericTitanic()
# create the models
comp <- GetModelComparisons(titanic[, -1], titanic[, 1], validation="50/50")
# predict the values for the dataset
pred.list <- predict(comp, titanic[, -1])
# check that there are the same number of predictions as there are models
expect_equal(length(comp$model.list), length(pred.list))
# ensure plot doesn't have any errors
plot(comp, titanic[, 1], titanic[, -1])
})
test_that("95/05 validation works", {
titanic <- PrepareNumericTitanic()
# create the models
comp <- GetModelComparisons(titanic[, -1], titanic[, 1], validation="95/05")
# predict the values for the dataset
pred.list <- predict(comp, titanic[, -1])
# check that there are the same number of predictions as there are models
expect_equal(length(comp$model.list), length(pred.list))
# ensure plot doesn't have any errors
plot(comp, titanic[, 1], titanic[, -1])
})
test_that("CV validation works", {
titanic <- PrepareNumericTitanic()
# create the models
comp <- GetModelComparisons(titanic[, -1], titanic[, 1], validation="cv")
# predict the values for the dataset
pred.list <- predict(comp, titanic[, -1])
# check that there are the same number of predictions as there are models
expect_equal(length(comp$model.list), length(pred.list))
# ensure plot doesn't have any errors
plot(comp, titanic[, 1], titanic[, -1])
})
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