def test_learner_scorer(self): data = Table('voting') learner = LogisticRegressionLearner() scores = learner.score_data(data) self.assertEqual('physician-fee-freeze', data.domain.attributes[np.argmax(scores)].name) self.assertEqual(len(scores), len(data.domain.attributes))
def test_learner_scorer_previous_transformation(self): learner = LogisticRegressionLearner() from Orange.preprocess import Discretize data = Discretize()(self.iris) scores = learner.score_data(data) # scores should be defined and positive self.assertTrue(np.all(scores > 0))
def test_learner_scorer_previous_transformation(self): learner = LogisticRegressionLearner() from Orange.preprocess import Discretize data = Discretize()(self.iris) scores = learner.score_data(data) # scores should be defined and positive self.assertTrue(np.all(scores > 0))
def test_learner_scorer(self): data = Table('voting') learner = LogisticRegressionLearner() scores = learner.score_data(data) self.assertEqual('physician-fee-freeze', data.domain.attributes[np.argmax(scores)].name) self.assertEqual(len(scores), len(data.domain.attributes))
def test_learner_scorer(self): learner = LogisticRegressionLearner() scores = learner.score_data(self.heart_disease) self.assertEqual( 'major vessels colored', self.heart_disease.domain.attributes[np.argmax(scores)].name) self.assertEqual(scores.shape, (1, len(self.heart_disease.domain.attributes)))
def test_learner_scorer(self): learner = LogisticRegressionLearner() scores = learner.score_data(self.voting) self.assertEqual( "physician-fee-freeze", self.voting.domain.attributes[np.argmax(scores)].name, ) self.assertEqual(scores.shape, (1, len(self.voting.domain.attributes)))
def test_learner_scorer_multiclass(self): attr = self.zoo.domain.attributes learner = LogisticRegressionLearner() scores = learner.score_data(self.zoo) self.assertEqual('aquatic', attr[np.argmax(scores[0])].name) # amphibian self.assertEqual('feathers', attr[np.argmax(scores[1])].name) # bird self.assertEqual('fins', attr[np.argmax(scores[2])].name) # fish self.assertEqual('legs', attr[np.argmax(scores[3])].name) # insect self.assertEqual('backbone', attr[np.argmax(scores[4])].name) # invertebrate self.assertEqual('milk', attr[np.argmax(scores[5])].name) # mammal self.assertEqual('hair', attr[np.argmax(scores[6])].name) # reptile self.assertEqual(scores.shape, (len(self.zoo.domain.class_var.values), len(attr)))
def test_learner_scorer_multiclass(self): attr = self.zoo.domain.attributes learner = LogisticRegressionLearner() scores = learner.score_data(self.zoo) self.assertEqual('aquatic', attr[np.argmax(scores[0])].name) self.assertEqual('feathers', attr[np.argmax(scores[1])].name) self.assertEqual('fins', attr[np.argmax(scores[2])].name) self.assertEqual('backbone', attr[np.argmax(scores[3])].name) self.assertEqual('backbone', attr[np.argmax(scores[4])].name) self.assertEqual('milk', attr[np.argmax(scores[5])].name) self.assertEqual('hair', attr[np.argmax(scores[6])].name) self.assertEqual(scores.shape, (len(self.zoo.domain.class_var.values), len(attr)))
def test_learner_scorer_multiclass(self): attr = self.zoo.domain.attributes learner = LogisticRegressionLearner() scores = learner.score_data(self.zoo) self.assertEqual('aquatic', attr[np.argmax(scores[0])].name) self.assertEqual('feathers', attr[np.argmax(scores[1])].name) self.assertEqual('fins', attr[np.argmax(scores[2])].name) self.assertEqual('backbone', attr[np.argmax(scores[3])].name) self.assertEqual('backbone', attr[np.argmax(scores[4])].name) self.assertEqual('milk', attr[np.argmax(scores[5])].name) self.assertEqual('hair', attr[np.argmax(scores[6])].name) self.assertEqual(scores.shape, (len(self.zoo.domain.class_var.values), len(attr)))
def test_learner_scorer_multiclass(self): attr = self.zoo.domain.attributes learner = LogisticRegressionLearner() scores = learner.score_data(self.zoo) self.assertEqual('aquatic', attr[np.argmax(scores[0])].name) # amphibian self.assertEqual('feathers', attr[np.argmax(scores[1])].name) # bird self.assertEqual('fins', attr[np.argmax(scores[2])].name) # fish self.assertEqual('legs', attr[np.argmax(scores[3])].name) # insect self.assertEqual('backbone', attr[np.argmax(scores[4])].name) # invertebrate self.assertEqual('milk', attr[np.argmax(scores[5])].name) # mammal self.assertEqual('hair', attr[np.argmax(scores[6])].name) # reptile self.assertEqual(scores.shape, (len(self.zoo.domain.class_var.values), len(attr)))
def test_learner_scorer_feature(self): learner = LogisticRegressionLearner() scores = learner.score_data(self.heart_disease) for i, attr in enumerate(self.heart_disease.domain.attributes): score = learner.score_data(self.heart_disease, attr) np.testing.assert_array_almost_equal(score, scores[:, i])
def test_learner_scorer_multiclass_feature(self): learner = LogisticRegressionLearner() scores = learner.score_data(self.zoo) for i, attr in enumerate(self.zoo.domain.attributes): score = learner.score_data(self.zoo, attr) np.testing.assert_array_almost_equal(score, scores[:, i])
def test_learner_scorer(self): learner = LogisticRegressionLearner() scores = learner.score_data(self.voting) self.assertEqual('physician-fee-freeze', self.voting.domain.attributes[np.argmax(scores)].name) self.assertEqual(scores.shape, (1, len(self.voting.domain.attributes)))
def test_learner_scorer(self): learner = LogisticRegressionLearner() scores = learner.score_data(self.heart_disease) self.assertEqual('major vessels colored', self.heart_disease.domain.attributes[np.argmax(scores)].name) self.assertEqual(scores.shape, (1, len(self.heart_disease.domain.attributes)))