Allow using RandomState object from Numpy in sklearn interface. (#5049)

2019-11-19 10:56:39 +08:00
parent 4d2779663e
commit a4f5c86276
2 changed files with 7 additions and 0 deletions
--- a/python-package/xgboost/sklearn.py
+++ b/python-package/xgboost/sklearn.py
@@ -230,6 +230,9 @@ class XGBModel(XGBModelBase):
            params['missing'] = None  # sklearn doesn't handle nan. see #4725
        if not params.get('eval_metric', True):
            del params['eval_metric']  # don't give as None param to Booster
+        if isinstance(params['random_state'], np.random.RandomState):
+            params['random_state'] = params['random_state'].randint(
+                np.iinfo(np.int32).max)
        return params

    def get_xgb_params(self):