Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

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

Browse Source 
* 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
Download Patch File Download Diff File Expand all files Collapse all files

3
demo/guide-python/custom_softmax.py
View File

@@ -142,7 +142,8 @@ def main(args):
native_results = {}
# Use the same objective function defined in XGBoost.
booster_native = xgb.train({'num_class': kClasses},
booster_native = xgb.train({'num_class': kClasses,
'eval_metric': 'merror'},
m,
num_boost_round=kRounds,
evals_result=native_results,