def test_scorer_feature(self):
np.random.seed(42)
data = Table('test4.tab')
learner = RandomForestLearner()
scores = learner.score_data(data)
for i, attr in enumerate(data.domain.attributes):
np.random.seed(42)
score = learner.score_data(data, attr)
np.testing.assert_array_almost_equal(score, scores[:, i])
def test_scorer_feature(self):
np.random.seed(42)
data = Table(test_filename('datasets/test4.tab'))
learner = RandomForestLearner()
scores = learner.score_data(data)
for i, attr in enumerate(data.domain.attributes):
np.random.seed(42)
score = learner.score_data(data, attr)
np.testing.assert_array_almost_equal(score, scores[:, i])
def test_scorer_feature(self):
np.random.seed(42)
data = Table('test4.tab')
learner = RandomForestLearner()
scores = learner.score_data(data)
for i, attr in enumerate(data.domain.attributes):
np.random.seed(42)
score = learner.score_data(data, attr)
self.assertEqual(score, scores[i])
def test_classification_scorer(self):
learner = RandomForestLearner()
scores = learner.score_data(self.iris)
self.assertEqual(scores.shape[1], len(self.iris.domain.attributes))
self.assertNotEqual(sum(scores[0]), 0)
self.assertEqual(['petal length', 'petal width'],
sorted([self.iris.domain.attributes[i].name
for i in np.argsort(scores[0])[-2:]]))
def test_classification_scorer(self):
learner = RandomForestLearner()
scores = learner.score_data(self.iris)
self.assertEqual(scores.shape[1], len(self.iris.domain.attributes))
self.assertNotEqual(sum(scores[0]), 0)
self.assertEqual(['petal length', 'petal width'],
sorted([self.iris.domain.attributes[i].name
for i in np.argsort(scores[0])[-2:]]))
def test_classification_scorer(self):
data = Table('iris')
learner = RandomForestLearner()
scores = learner.score_data(data)
self.assertEqual(len(scores), len(data.domain.attributes))
self.assertNotEqual(sum(scores), 0)
self.assertEqual(['petal length', 'petal width'],
sorted([data.domain.attributes[i].name
for i in np.argsort(scores)[-2:]]))
def test_classification_scorer(self):
data = Table('iris')
learner = RandomForestLearner()
scores = learner.score_data(data)
self.assertEqual(len(scores), len(data.domain.attributes))
self.assertNotEqual(sum(scores), 0)
self.assertEqual(['petal length', 'petal width'],
sorted([
data.domain.attributes[i].name
for i in np.argsort(scores)[-2:]
]))
