コード例 #1
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 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))
コード例 #2
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 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))
コード例 #3
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 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))
コード例 #4
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 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))
コード例 #5
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 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)))
コード例 #6
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 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)))
コード例 #7
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 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)))
コード例 #8
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 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)))
コード例 #9
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 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)))
コード例 #10
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 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)))
コード例 #11
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 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])
コード例 #12
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 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])
コード例 #13
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 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)))
コード例 #14
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 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)))