'Check learner and model for various values of all parameters
when pruning parameters are not checked'

def test_selected_learner(self):

    self.send_signal(self.widget.Inputs.evaluation_results, self.results_2_iris)
    self.assertEqual(self.widget.selected_learner, [0])
    self.widget.selected_learner[:] = [1]
    self.send_signal(self.widget.Inputs.evaluation_results, self.results_2_titanic)
    self.widget.selected_learner[:] = [1]
    self.send_signal(self.widget.Inputs.evaluation_results, self.results_1_iris)
    self.widget.selected_learner[:] = [0]
    self.send_signal(self.widget.Inputs.evaluation_results, None)
    self.send_signal(self.widget.Inputs.evaluation_results, self.results_1_iris)
    self.widget.selected_learner[:] = [0]
