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Add the missing max_delta_step (#3668)

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* add max_delta_step to SplitEvaluator

* test for max_delta_step

* missing x2 factor for L1 term

* remove gamma from ElasticNet
This commit is contained in:
Vadim Khotilovich
2018-09-12 08:43:41 -05:00
committed by GitHub
parent d1e75d615e
commit ad3a0bbab8
2 changed files with 35 additions and 10 deletions
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14
R-package/tests/testthat/test_basic.R
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@@ -223,3 +223,17 @@ test_that("train and predict with non-strict classes", {
expect_error(pr <- predict(bst, train_dense), regexp = NA)
expect_equal(pr0, pr)
})
test_that("max_delta_step works", {
dtrain <- xgb.DMatrix(agaricus.train$data, label = agaricus.train$label)
watchlist <- list(train = dtrain)
param <- list(objective = "binary:logistic", eval_metric="logloss", max_depth = 2, nthread = 2, eta = 0.5)
nrounds = 5
# model with no restriction on max_delta_step
bst1 <- xgb.train(param, dtrain, nrounds, watchlist, verbose = 1)
# model with restricted max_delta_step
bst2 <- xgb.train(param, dtrain, nrounds, watchlist, verbose = 1, max_delta_step = 1)
# the no-restriction model is expected to have consistently lower loss during the initial interations
expect_true(all(bst1$evaluation_log$train_logloss < bst2$evaluation_log$train_logloss))
expect_lt(mean(bst1$evaluation_log$train_logloss)/mean(bst2$evaluation_log$train_logloss), 0.8)
})