FIX default parameter value of min_samples_leaf in BalancedRandomForestClassifier (#711)

Co-authored-by: Guillaume Lemaitre <[email protected]>

Author: zerolfx

doc/whats_new/v0.7.rst

@@ -5,3 +5,17 @@ Version 0.7.0 (under development)
 
 Changelog
 ---------
+
+Changed models
+..............
+
+The following models might give some different results due to changes:
+
+- :class:`imblearn.ensemble.BalancedRandomForestClassifier`
+
+Bug fixes
+.........
+
+- Change the default value `min_samples_leaf` to be consistent with
+  scikit-learn.
+  :pr:`711` by :user:`zerolfx <zerolfx>`.

imblearn/ensemble/_forest.py

@@ -302,7 +302,7 @@ def __init__(
         criterion="gini",
         max_depth=None,
         min_samples_split=2,
-        min_samples_leaf=2,
+        min_samples_leaf=1,
         min_weight_fraction_leaf=0.0,
         max_features="auto",
         max_leaf_nodes=None,

imblearn/ensemble/tests/test_forest.py

@@ -116,7 +116,8 @@ def test_balanced_random_forest_oob(imbalanced_dataset):
         X, y, random_state=42, stratify=y
     )
     est = BalancedRandomForestClassifier(
-        oob_score=True, random_state=0, n_estimators=1000
+        oob_score=True, random_state=0, n_estimators=1000,
+        min_samples_leaf=2,
     )
 
     est.fit(X_train, y_train)