Nothing
context("Check aggregate_profiles() functions")
library("DALEX")
library("ranger")
titanic_small <- titanic_imputed[1:500,]
rf_model <- ranger(survived ~ gender + age + class + embarked +
fare + sibsp + parch, data = titanic_small,
probability = TRUE)
explainer_rf <- explain(rf_model, data = titanic_small,
y = titanic_small$survived,
label = "RF", verbose = FALSE)
test_that("plot aggregate_profiles",{
selected_passangers_10 <- select_neighbours(titanic_small, titanic_small[1,], n = 10)
selected_passangers <- select_sample(titanic_small, n = 100)
cp_rf <- ceteris_paribus(explainer_rf, selected_passangers)
pdp_rf_p <- aggregate_profiles(cp_rf, variables = "age", type = "partial")
pdp_rf_p$`_label_` <- "RF_partial"
pdp_rf_c <- aggregate_profiles(cp_rf, variables = "age", type = "conditional")
pdp_rf_c$`_label_` <- "RF_conditional"
pdp_rf_a <- aggregate_profiles(cp_rf, variables = "age", type = "accumulated")
pdp_rf_a$`_label_` <- "RF_accumulated"
pl1 <- plot(pdp_rf_p, pdp_rf_c, pdp_rf_a, color = "_label_")
expect_true("gg" %in% class(pl1))
pdp_rf_p <- partial_dependence(explainer_rf, variables = "age")
pdp_rf_p$`_label_` <- "RF_partial"
pdp_rf_c <- conditional_dependence(explainer_rf, variables = "age")
pdp_rf_c$`_label_` <- "RF_conditional"
pdp_rf_a <- accumulated_dependence(explainer_rf, variables = "age")
pdp_rf_a$`_label_` <- "RF_accumulated"
pl2 <- plot(pdp_rf_p, pdp_rf_c, pdp_rf_a, color = "_label_")
expect_true("gg" %in% class(pl2))
expect_error(aggregate_profiles(explainer_rf, variable_type = "wrong"))
})
test_that("plot partial_dependence",{
selected_passangers <- select_sample(titanic, n = 100)
cp_rf <- ceteris_paribus(explainer_rf, selected_passangers)
res <- partial_dependence(explainer_rf, N=50, variables = "gender", variable_type = "categorical")
expect_true("aggregated_profiles_explainer" %in% class(res))
})
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