e91a752ee0c7a903af2fa85aa558222eed15d549,Orange/widgets/classify/tests/test_owclassificationtree.py,TestOWClassificationTree,setUp,#TestOWClassificationTree#,9

Before Change



        scores = [score[1] for score in self.widget.scores]
        md_spin = self.widget.max_depth_spin[1]
        mi_spin = self.widget.min_internal_spin[1]
        ml_spin = self.widget.min_leaf_spin[1]
        md_min_max = [md_spin.minimum(), md_spin.maximum()]
        mi_min_max = [mi_spin.minimum(), mi_spin.maximum()]
        ml_min_max = [ml_spin.minimum(), ml_spin.maximum()]
        self.gui_to_params = [
            GuiToParam("criterion", self.widget.score_combo,
                       lambda x: scores[x.currentIndex()],
                       combo_set_value, scores, list(range(len(scores)))),
            GuiToParam("max_depth", md_spin, lambda x: x.value(),
                       lambda i, x: x.setValue(i), md_min_max, md_min_max),
            GuiToParam("min_samples_split", mi_spin, lambda x: x.value(),
                       lambda i, x: x.setValue(i), mi_min_max, mi_min_max),
            GuiToParam("min_samples_leaf", ml_spin, lambda x: x.value(),
                       lambda i, x: x.setValue(i), ml_min_max, ml_min_max)]

    def test_parameters_unchecked(self):
        Check learner and model for various values of all parameters
        when pruning parameters are not checked

After Change


                                         stored_settings={"auto_apply": False})
        self.init()
        scores = [score[1] for score in self.widget.scores]
        self.parameters = [
            ParameterMapping("criterion", self.widget.score_combo, scores),
            ParameterMapping("max_depth", self.widget.max_depth_spin[1]),
            ParameterMapping("min_samples_split",
                             self.widget.min_internal_spin[1]),
            ParameterMapping("min_samples_leaf", self.widget.min_leaf_spin[1])]

    def test_parameters_unchecked(self):
        Check learner and model for various values of all parameters
        when pruning parameters are not checked
Italian Trulli
In pattern: SUPERPATTERN

Frequency: 3

Non-data size: 28

Instances


Project Name: biolab/orange3
Commit Name: e91a752ee0c7a903af2fa85aa558222eed15d549
Time: 2016-08-05
Author: tankovesna@hotmail.com
File Name: Orange/widgets/classify/tests/test_owclassificationtree.py
Class Name: TestOWClassificationTree
Method Name: setUp


Project Name: biolab/orange3
Commit Name: e91a752ee0c7a903af2fa85aa558222eed15d549
Time: 2016-08-05
Author: tankovesna@hotmail.com
File Name: Orange/widgets/regression/tests/test_owregressiontree.py
Class Name: TestOWRegressionTree
Method Name: setUp


Project Name: biolab/orange3
Commit Name: e91a752ee0c7a903af2fa85aa558222eed15d549
Time: 2016-08-05
Author: tankovesna@hotmail.com
File Name: Orange/widgets/classify/tests/test_owclassificationtree.py
Class Name: TestOWClassificationTree
Method Name: setUp


Project Name: biolab/orange3
Commit Name: e91a752ee0c7a903af2fa85aa558222eed15d549
Time: 2016-08-05
Author: tankovesna@hotmail.com
File Name: Orange/widgets/regression/tests/test_owadaboostregression.py
Class Name: TestOWAdaBoostRegression
Method Name: setUp