[FIX] Tree: Reintroduce preprocessors.

Orange/classification/tree.py

@@ -58,8 +58,8 @@ class TreeLearner(Learner):
     def __init__(
             self, *args, binarize=False, max_depth=None,
             min_samples_leaf=1, min_samples_split=2, sufficient_majority=0.95,
-            **kwargs):
-        super().__init__(*args, **kwargs)
+            preprocessors=None, **kwargs):
+        super().__init__(preprocessors=preprocessors)
         self.params = {}
         self.binarize = self.params['binarize'] = binarize
         self.min_samples_leaf = self.params['min_samples_leaf'] = min_samples_leaf

Orange/tests/test_tree.py

@@ -2,17 +2,18 @@
 # pylint: disable=missing-docstring
 
 import unittest
+from unittest.mock import Mock
 
 import numpy as np
 import sklearn.tree as skl_tree
 from sklearn.tree._tree import TREE_LEAF
 
 from Orange.data import Table
-from Orange.classification import SklTreeLearner
+from Orange.classification import SklTreeLearner, TreeLearner
 from Orange.regression import SklTreeRegressionLearner
 
 
-class TestTreeLearner(unittest.TestCase):
+class TestSklTreeLearner(unittest.TestCase):
     def test_classification(self):
         table = Table('iris')
         learn = SklTreeLearner()
@@ -28,6 +29,16 @@ def test_regression(self):
         self.assertTrue(np.all(table.Y.flatten() == pred))
 
 
+class TestTreeLearner(unittest.TestCase):
+    def test_uses_preprocessors(self):
+        iris = Table('iris')
+        mock_preprocessor = Mock(return_value=iris)
+
+        tree = TreeLearner(preprocessors=[mock_preprocessor])
+        tree(iris)
+        mock_preprocessor.assert_called_with(iris)
+
+
 class TestDecisionTreeClassifier(unittest.TestCase):
     @classmethod
     def setUpClass(cls):