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[Breaking] Change default evaluation metric for classification to logloss / mlogloss (#6183)

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* Change DefaultEvalMetric of classification from error to logloss

* Change default binary metric in plugin/example/custom_obj.cc

* Set old error metric in python tests

* Set old error metric in R tests

* Fix missed eval metrics and typos in R tests

* Fix setting eval_metric twice in R tests

* Add warning for empty eval_metric for classification

* Fix Dask tests

Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Christian Lorentzen
2020-10-02 21:06:47 +02:00
committed by GitHub
parent e0e4f15d0e
commit cf4f019ed6
18 changed files with 56 additions and 32 deletions
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8
tests/python/test_basic_models.py
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@@ -117,7 +117,8 @@ class TestModels(unittest.TestCase):
# learning_rates as a list
# init eta with 0 to check whether learning_rates work
param = {'max_depth': 2, 'eta': 0, 'verbosity': 0,
'objective': 'binary:logistic', 'tree_method': tree_method}
'objective': 'binary:logistic', 'eval_metric': 'error',
'tree_method': tree_method}
evals_result = {}
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[xgb.callback.reset_learning_rate([
@@ -131,7 +132,8 @@ class TestModels(unittest.TestCase):
# init learning_rate with 0 to check whether learning_rates work
param = {'max_depth': 2, 'learning_rate': 0, 'verbosity': 0,
'objective': 'binary:logistic', 'tree_method': tree_method}
'objective': 'binary:logistic', 'eval_metric': 'error',
'tree_method': tree_method}
evals_result = {}
bst = xgb.train(param, dtrain, num_round, watchlist,
callbacks=[xgb.callback.reset_learning_rate(
@@ -145,7 +147,7 @@ class TestModels(unittest.TestCase):
# check if learning_rates override default value of eta/learning_rate
param = {
'max_depth': 2, 'verbosity': 0, 'objective': 'binary:logistic',
'tree_method': tree_method
'eval_metric': 'error', 'tree_method': tree_method
}
evals_result = {}
bst = xgb.train(param, dtrain, num_round, watchlist,