Merge pull request #2135 from pavlin-policar/fix-sgd-defaults

SGD: Fix default loss parameter

Author: janezd

Orange/classification/sgd.py

@@ -13,7 +13,7 @@ class SGDClassificationLearner(SklLearner):
     __returns__ = LinearModel
     preprocessors = SklLearner.preprocessors + [Normalize()]
 
-    def __init__(self, loss='squared_loss',penalty='l2', alpha=0.0001,
+    def __init__(self, loss='hinge', penalty='l2', alpha=0.0001,
                  l1_ratio=0.15,fit_intercept=True, n_iter=5, shuffle=True,
                  epsilon=0.1, random_state=None, learning_rate='invscaling',
                  eta0=0.01, power_t=0.25, warm_start=False, average=False,

Orange/regression/linear.py

@@ -83,7 +83,7 @@ class SGDRegressionLearner(LinearRegressionLearner):
     __wraps__ = skl_linear_model.SGDRegressor
     preprocessors = SklLearner.preprocessors + [Normalize()]
 
-    def __init__(self, loss='squared_loss',penalty='l2', alpha=0.0001,
+    def __init__(self, loss='squared_loss', penalty='l2', alpha=0.0001,
                  l1_ratio=0.15, fit_intercept=True, n_iter=5, shuffle=True,
                  epsilon=0.1, n_jobs=1, random_state=None,
                  learning_rate='invscaling', eta0=0.01, power_t=0.25,

Orange/tests/test_sgd.py

@@ -35,7 +35,7 @@ def setUpClass(cls):
     def test_SGDClassification(self):
         sgd = SGDClassificationLearner()
         res = CrossValidation(self.iris, [sgd], k=3)
-        self.assertGreater(AUC(res)[0], 0.85)
+        self.assertGreater(AUC(res)[0], 0.8)
 
     def test_coefficients(self):
         lrn = SGDClassificationLearner()