Merge pull request #2392 from jerneju/value-logisticregression

[FIX] Logistic Regression: impute

Orange/base.py

@@ -117,6 +117,7 @@ def __call__(self, data):
 
         self.domain = data.domain
         model = self._fit_model(data)
+        model.used_vals = [np.unique(y) for y in data.Y[:, None].T]
         model.domain = data.domain
         model.supports_multiclass = self.supports_multiclass
         model.name = self.name
@@ -377,7 +378,6 @@ def preprocess(self, data):
 
     def __call__(self, data):
         m = super().__call__(data)
-        m.used_vals = [np.unique(y) for y in data.Y[:, None].T]
         m.params = self.params
         return m
 

Orange/widgets/model/tests/test_owlogisticregression.py

@@ -2,6 +2,8 @@
 # pylint: disable=missing-docstring
 import unittest
 
+import numpy as np
+
 from Orange.classification import LogisticRegressionLearner
 from Orange.data import Table, Domain, ContinuousVariable, DiscreteVariable
 from Orange.statistics.util import stats
@@ -95,3 +97,17 @@ def test_coefficients_one_value(self):
         coef = self.get_output("Coefficients")
         self.assertEqual(coef.domain[0].name, "no")
         self.assertGreater(coef[2][0], 0.)
+
+    def test_target_with_nan(self):
+        """
+        Rows with targets with nans are removed.
+        GH-2392
+        """
+        table = Table("iris")
+        table.Y[5:10] = np.NaN
+        self.send_signal("Data", table)
+        coef1 = self.get_output("Coefficients")
+        del table[5:10]
+        self.send_signal("Data", table)
+        coef2 = self.get_output("Coefficients")
+        self.assertTrue(np.array_equal(coef1, coef2))