FIX properly set the default n_neighbours in SMOTE svm and borderline (#578)

Author: glemaitre

doc/whats_new/v0.5.rst

@@ -64,6 +64,11 @@ Bug
   estimator.
   :pr:`554` by :user:`Oliver Rausch <orausch>`.
 
+- Fix bug in :class:`imblearn.over_sampling.SVMSMOTE` and
+  :class:`imblearn.over_sampling.BorderlineSMOTE` where the default parameter
+  of ``n_neighbors`` was not set properly.
+  :pr:`578` by :user:`Guillaume Lemaitre <glemaitre>`.
+
 - Fix bug by changing the default depth in
   :class:`imblearn.ensemble.RUSBoostClassifier` to get a decision stump as a
   weak learner as in the original paper.

imblearn/over_sampling/_smote.py

@@ -323,7 +323,7 @@ def __init__(self,
     def _validate_estimator(self):
         super()._validate_estimator()
         self.nn_m_ = check_neighbors_object(
-            'k_neighbors', self.k_neighbors, additional_neighbor=1)
+            'm_neighbors', self.m_neighbors, additional_neighbor=1)
         self.nn_m_.set_params(**{'n_jobs': self.n_jobs})
         if self.kind not in ('borderline-1', 'borderline-2'):
             raise ValueError('The possible "kind" of algorithm are '
@@ -506,7 +506,7 @@ def __init__(self,
     def _validate_estimator(self):
         super()._validate_estimator()
         self.nn_m_ = check_neighbors_object(
-            'k_neighbors', self.k_neighbors, additional_neighbor=1)
+            'm_neighbors', self.m_neighbors, additional_neighbor=1)
         self.nn_m_.set_params(**{'n_jobs': self.n_jobs})
 
         if self.svm_estimator is None:

imblearn/over_sampling/tests/test_smote.py

@@ -11,6 +11,8 @@
 from sklearn.svm import SVC
 
 from imblearn.over_sampling import SMOTE
+from imblearn.over_sampling import SVMSMOTE
+from imblearn.over_sampling import BorderlineSMOTE
 
 
 RND_SEED = 0
@@ -286,3 +288,14 @@ def test_sample_with_nn_svm():
                      1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0])
     assert_allclose(X_resampled, X_gt, rtol=R_TOL)
     assert_array_equal(y_resampled, y_gt)
+
+
+@pytest.mark.parametrize(
+    "smote", [BorderlineSMOTE(), SVMSMOTE()], ids=['borderline', 'svm']
+)
+def test_smote_m_neighbors(smote):
+    # check that m_neighbors is properly set. Regression test for:
+    # https://github.com/scikit-learn-contrib/imbalanced-learn/issues/568
+    _ = smote.fit_resample(X, Y)
+    assert smote.nn_k_.n_neighbors == 6
+    assert smote.nn_m_.n_neighbors == 11