Merge pull request #1448 from sstanovnik/fix-logreg-weights

[FIX] Stop advertising support for weights in LogisticRegression.

Author: lanzagar

Orange/classification/logistic_regression.py

@@ -41,3 +41,8 @@ def __init__(self, penalty="l2", dual=False, tol=0.0001, C=1.0,
                  random_state=None, preprocessors=None):
         super().__init__(preprocessors=preprocessors)
         self.params = vars()
+
+    @property
+    def supports_weights(self):
+        # liblinear (default) cannot handle weights
+        return False

Orange/tests/test_base.py

@@ -3,7 +3,11 @@
 import unittest
 
 from Orange.base import SklLearner
+from Orange.regression import LinearRegressionLearner
 from Orange.classification import LogisticRegressionLearner
+from Orange.data import Table
+
+from sklearn.linear_model import LogisticRegression
 
 
 class TestSklLearner(unittest.TestCase):
@@ -26,7 +30,19 @@ class DummyLearner(SklLearner):
 
         self.assertFalse(DummyLearner().supports_weights)
 
-    def test_logreg(self):
-        self.assertTrue(LogisticRegressionLearner().supports_weights,
-                        "Either LogisticRegression no longer supports weighted tables"
+    def test_linreg(self):
+        self.assertTrue(LinearRegressionLearner().supports_weights,
+                        "Either LinearRegression no longer supports weighted tables "
                         "or SklLearner.supports_weights is out-of-date.")
+
+    def test_logreg(self):
+        self.assertFalse(LogisticRegressionLearner().supports_weights,
+                         "Logistic regression has its supports_weights overridden because "
+                         "liblinear doesn't support them (even though the parameter exists)")
+
+    def test_assert_liblinear_doesnt_accept_weights(self):
+        data = Table('iris')
+        data.set_weights(1.2)
+        with self.assertRaises(ValueError):
+            skl = LogisticRegression(solver='liblinear')
+            skl.fit(data.X, data.Y, data.W)