removed cross_val_Score

kaichogami · kaichogami · commit e19ed6ac535c · 2016-09-17T21:57:25.000+05:30
diff --git a/doc/whats_new.rst b/doc/whats_new.rst
@@ -203,6 +203,8 @@ API
 
     - :func:`mne.preprocessing.create_ecg_epochs` now includes all the channels when ``picks=None`` by `Jaakko Leppakangas`_
 
+    - Added functionality to change scoring method in :class:`mne.decoding.SearchLight` by `Asish Panda`_
+
 .. _changes_0_12:
 
 Version 0.12
diff --git a/mne/decoding/search_light.py b/mne/decoding/search_light.py
@@ -4,12 +4,12 @@
 
 import numpy as np
 
+from sklearn.metrics import make_scorer
+
 from .mixin import TransformerMixin
 from .base import BaseEstimator, _check_estimator
 from ..parallel import parallel_func
 
-from sklearn.metrics import make_scorer
-
 
 class SearchLight(BaseEstimator, TransformerMixin):
     """Search Light.
diff --git a/mne/decoding/tests/test_search_light.py b/mne/decoding/tests/test_search_light.py
@@ -10,8 +10,7 @@
 from ..search_light import SearchLight, GeneralizationLight
 from .. import Vectorizer
 
-from sklearn.metrics import accuracy_score, roc_auc_score
-from sklearn.cross_validation import cross_val_score
+from sklearn.metrics import roc_auc_score
 
 def make_data():
     n_epochs, n_chan, n_time = 50, 32, 10
@@ -63,8 +62,6 @@ def test_searchlight():
     score = sl.score(X, y)
     assert_array_equal(score.shape, [n_time])
     assert_true(score.dtype == float)
-    sl = SearchLight(LogisticRegression())
-    assert_array_equal(cross_val_score(sl, X, y, scoring='roc_auc'), score)
 
     # n_jobs
     sl = SearchLight(LogisticRegression(), n_jobs=2)
