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[R] rename Quality -> Gain (#9938)

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This commit is contained in:
david-cortes
2023-12-31 06:01:00 +01:00
committed by GitHub
parent 8b9c98b65b
commit 73713de601
7 changed files with 22 additions and 22 deletions
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4
R-package/tests/testthat/test_helpers.R
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@@ -275,7 +275,7 @@ test_that("xgb.Booster serializing as R object works", {
test_that("xgb.model.dt.tree works with and without feature names", {
.skip_if_vcd_not_available()
names.dt.trees <- c("Tree", "Node", "ID", "Feature", "Split", "Yes", "No", "Missing", "Quality", "Cover")
names.dt.trees <- c("Tree", "Node", "ID", "Feature", "Split", "Yes", "No", "Missing", "Gain", "Cover")
dt.tree <- xgb.model.dt.tree(feature_names = feature.names, model = bst.Tree)
expect_equal(names.dt.trees, names(dt.tree))
if (!flag_32bit)
@@ -341,7 +341,7 @@ test_that("xgb.importance works with and without feature names", {
trees = trees
)[
Feature != "Leaf", .(
Gain = sum(Quality),
Gain = sum(Gain),
Cover = sum(Cover),
Frequency = .N
),

16
R-package/tests/testthat/test_update.R
View File

@@ -53,9 +53,9 @@ test_that("updating the model works", {
# should be the same evaluation but different gains and larger cover
expect_equal(bst2$evaluation_log, bst2r$evaluation_log)
if (!win32_flag) {
expect_equal(tr2[Feature == 'Leaf']$Quality, tr2r[Feature == 'Leaf']$Quality)
expect_equal(tr2[Feature == 'Leaf']$Gain, tr2r[Feature == 'Leaf']$Gain)
}
expect_gt(sum(abs(tr2[Feature != 'Leaf']$Quality - tr2r[Feature != 'Leaf']$Quality)), 100)
expect_gt(sum(abs(tr2[Feature != 'Leaf']$Gain - tr2r[Feature != 'Leaf']$Gain)), 100)
expect_gt(sum(tr2r$Cover) / sum(tr2$Cover), 1.5)
# process type 'update' for no-subsampling model, refreshing the tree stats AND leaves from training data:
@@ -72,8 +72,8 @@ test_that("updating the model works", {
tr2u <- xgb.model.dt.tree(model = bst2u)
# should be the same evaluation but different gains and larger cover
expect_equal(bst2$evaluation_log, bst2u$evaluation_log)
expect_equal(tr2[Feature == 'Leaf']$Quality, tr2u[Feature == 'Leaf']$Quality)
expect_gt(sum(abs(tr2[Feature != 'Leaf']$Quality - tr2u[Feature != 'Leaf']$Quality)), 100)
expect_equal(tr2[Feature == 'Leaf']$Gain, tr2u[Feature == 'Leaf']$Gain)
expect_gt(sum(abs(tr2[Feature != 'Leaf']$Gain - tr2u[Feature != 'Leaf']$Gain)), 100)
expect_gt(sum(tr2u$Cover) / sum(tr2$Cover), 1.5)
# the results should be the same as for the model with an extra 'refresh' updater
expect_equal(bst2r$evaluation_log, bst2u$evaluation_log)
@@ -87,8 +87,8 @@ test_that("updating the model works", {
tr1ut <- xgb.model.dt.tree(model = bst1ut)
# should be the same evaluations but different gains and smaller cover (test data is smaller)
expect_equal(bst1$evaluation_log, bst1ut$evaluation_log)
expect_equal(tr1[Feature == 'Leaf']$Quality, tr1ut[Feature == 'Leaf']$Quality)
expect_gt(sum(abs(tr1[Feature != 'Leaf']$Quality - tr1ut[Feature != 'Leaf']$Quality)), 100)
expect_equal(tr1[Feature == 'Leaf']$Gain, tr1ut[Feature == 'Leaf']$Gain)
expect_gt(sum(abs(tr1[Feature != 'Leaf']$Gain - tr1ut[Feature != 'Leaf']$Gain)), 100)
expect_lt(sum(tr1ut$Cover) / sum(tr1$Cover), 0.5)
})
@@ -111,7 +111,7 @@ test_that("updating works for multiclass & multitree", {
# should be the same evaluation but different gains and larger cover
expect_equal(bst0$evaluation_log, bst0u$evaluation_log)
expect_equal(tr0[Feature == 'Leaf']$Quality, tr0u[Feature == 'Leaf']$Quality)
expect_gt(sum(abs(tr0[Feature != 'Leaf']$Quality - tr0u[Feature != 'Leaf']$Quality)), 100)
expect_equal(tr0[Feature == 'Leaf']$Gain, tr0u[Feature == 'Leaf']$Gain)
expect_gt(sum(abs(tr0[Feature != 'Leaf']$Gain - tr0u[Feature != 'Leaf']$Gain)), 100)
expect_gt(sum(tr0u$Cover) / sum(tr0$Cover), 1.5)
})