Fix to sparse SVC with kernel='poly'

Author: Amit Aides

scikits/learn/svm/sparse/base.py

@@ -102,7 +102,7 @@ def fit(self, X, y, class_weight={}, sample_weight=[], **params):
         self.class_weight, self.class_weight_label = \
                      _get_class_weight(class_weight, y)
 
-        if (kernel_type == 2) and (self.gamma == 0):
+        if (kernel_type in [1, 2]) and (self.gamma == 0):
             # if custom gamma is not provided ...
             self.gamma = 1.0 / X.shape[0]
 

scikits/learn/svm/tests/test_sparse.py

@@ -60,7 +60,7 @@ def test_SVC():
 
 def test_SVC_iris():
     """Test the sparse SVC with the iris dataset"""
-    for k in ('linear', 'rbf'):
+    for k in ('linear', 'poly', 'rbf'):
         sp_clf = svm.sparse.SVC(kernel=k).fit(iris.data, iris.target)
         clf = svm.SVC(kernel=k).fit(iris.data.todense(), iris.target)