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[R] Avoid modifying importance dt in-place, fix aggregation (#9740)

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david-cortes 2023-10-31 22:10:59 +01:00 committed by GitHub
parent bc995a4865
commit d3f0646779
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2 changed files with 20 additions and 1 deletions
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8
R-package/R/xgb.plot.importance.R
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@ -87,7 +87,13 @@ xgb.plot.importance <- function(importance_matrix = NULL, top_n = NULL, measure
}
# also aggregate, just in case when the values were not yet summed up by feature
importance_matrix <- importance_matrix[, Importance := sum(get(measure)), by = Feature]
importance_matrix <- importance_matrix[
, lapply(.SD, sum)
, .SDcols = setdiff(names(importance_matrix), "Feature")
, by = Feature
][
, Importance := get(measure)
]
# make sure it's ordered
importance_matrix <- importance_matrix[order(-abs(Importance))]

13
R-package/tests/testthat/test_helpers.R
View File

@ -382,6 +382,9 @@ test_that("xgb.importance works with GLM model", {
expect_equal(colnames(imp2plot), c("Feature", "Weight", "Importance"))
xgb.ggplot.importance(importance.GLM)
# check that the input is not modified in-place
expect_false("Importance" %in% names(importance.GLM))
# for multiclass
imp.GLM <- xgb.importance(model = mbst.GLM)
expect_equal(dim(imp.GLM), c(12, 3))
@ -400,6 +403,16 @@ test_that("xgb.model.dt.tree and xgb.importance work with a single split model",
expect_equal(imp$Gain, 1)
})
test_that("xgb.plot.importance de-duplicates features", {
importances <- data.table(
Feature = c("col1", "col2", "col2"),
Gain = c(0.4, 0.3, 0.3)
)
imp2plot <- xgb.plot.importance(importances)
expect_equal(nrow(imp2plot), 2L)
expect_equal(imp2plot$Feature, c("col2", "col1"))
})
test_that("xgb.plot.tree works with and without feature names", {
.skip_if_vcd_not_available()
expect_silent(xgb.plot.tree(feature_names = feature.names, model = bst.Tree))