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)))
