Nothing
library(tidyverse)
library(tidymodels)
library(SSLR)
context("Testing DecisionTree")
source("wine.R")
m <- SSLRDecisionTree()
test_that(
desc = "DecisionTree model",
code = {
expect_is(m,"model_sslr")
}
)
test_that(
desc = "DecisionTree args",
code = {
expect_equal(m$args$max_depth,30)
expect_equal(m$args$w,0.5)
expect_equal(m$args$min_samples_split,20)
expect_equal(m$args$min_samples_leaf,7)
}
)
model <- m %>% fit(Wine ~ ., data = wine$train)
test_that(
desc = "DecisionTree fit",
code = {
expect_is(model,"model_sslr_fitted")
expect_equal(model$model$mode,"classification")
}
)
test_that(
desc = "DecisionTree predictions data frame",
code = {
predictions_frame <- predict(model,wine$test)
expect_is(predictions_frame,"data.frame")
}
)
test_that(
desc = "DecisionTree predictions factor",
code = {
predictions_factor <- predict(model,wine$test, type = "raw")
expect_is(predictions_factor,"factor")
expect_equal(length(predictions_factor),nrow(wine$test))
}
)
test_that(
desc = "DecisionTree predictions probabilities",
code = {
predictions_frame <- predict(model,wine$test,type = "prob")
expect_is(predictions_frame,"data.frame")
}
)
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