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Fix early stopping with linear model. (#7554)

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Jiaming Yuan
2022-01-13 21:53:06 +08:00
committed by GitHub
parent e5e47c3c99
commit e94b766310
2 changed files with 33 additions and 6 deletions
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28
R-package/tests/testthat/test_glm.R
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@@ -46,3 +46,31 @@ test_that("gblinear works", {
expect_equal(dim(h), c(n, ncol(dtrain) + 1))
expect_s4_class(h, "dgCMatrix")
})
test_that("gblinear early stopping works", {
data(agaricus.train, package = 'xgboost')
data(agaricus.test, package = 'xgboost')
dtrain <- xgb.DMatrix(agaricus.train$data, label = agaricus.train$label)
dtest <- xgb.DMatrix(agaricus.test$data, label = agaricus.test$label)
param <- list(
objective = "binary:logistic", eval_metric = "error", booster = "gblinear",
nthread = 2, eta = 0.8, alpha = 0.0001, lambda = 0.0001,
updater = "coord_descent"
)
es_round <- 1
n <- 10
booster <- xgb.train(
param, dtrain, n, list(eval = dtest, train = dtrain), early_stopping_rounds = es_round
)
expect_equal(booster$best_iteration, 5)
predt_es <- predict(booster, dtrain)
n <- booster$best_iteration + es_round
booster <- xgb.train(
param, dtrain, n, list(eval = dtest, train = dtrain), early_stopping_rounds = es_round
)
predt <- predict(booster, dtrain)
expect_equal(predt_es, predt)
})