Add test case in test_pipeline.

sklearn/tests/test_pipeline.py

@@ -23,7 +23,7 @@
 
 from sklearn.base import clone, BaseEstimator
 from sklearn.pipeline import Pipeline, FeatureUnion, make_pipeline, make_union
-from sklearn.svm import SVC
+from sklearn.svm import OneClassSVM, SVC
 from sklearn.linear_model import LogisticRegression, Lasso
 from sklearn.linear_model import LinearRegression
 from sklearn.cluster import KMeans
@@ -332,6 +332,17 @@ def test_pipeline_methods_pca_svm():
     pipe.score(X, y)
 
 
+def test_pipeline_score_samples_pca_oneclass_svm():
+    iris = load_iris()
+    X= iris.data
+    # Test with PCA + OneClassSVM
+    clf = OneClassSVM()
+    pca = PCA(svd_solver='full', n_components='mle', whiten=True)
+    pipe = Pipeline([('pca', pca), ('oneclass_svm', clf)])
+    pipe.fit(X)
+    pipe.score_samples(X)
+
+
 def test_pipeline_methods_preprocessing_svm():
     # Test the various methods of the pipeline (preprocessing + svm).
     iris = load_iris()