def test_augmented_data_regression(self):
data = Table("housing")
res = CrossValidation(store_data=True)(data,
[LinearRegressionLearner()])
table = res.get_augmented_data(['Linear Regression'])
self.assertEqual(len(table), len(data))
self.assertEqual(len(table.domain.attributes),
len(data.domain.attributes))
self.assertEqual(len(table.domain.class_vars),
len(data.domain.class_vars))
# +1 for class, +1 for fold
self.assertEqual(len(table.domain.metas),
len(data.domain.metas) + 1 + 1)
res = CrossValidation(store_data=True)(
data, [LinearRegressionLearner(),
MeanLearner()])
table = res.get_augmented_data(['Linear Regression', 'Mean Learner'])
self.assertEqual(len(table), len(data))
self.assertEqual(len(table.domain.attributes),
len(data.domain.attributes))
self.assertEqual(len(table.domain.class_vars),
len(data.domain.class_vars))
# +2 for class, +1 for fold
self.assertEqual(len(table.domain.metas),
len(data.domain.metas) + 2 + 1)
def test_augmented_data_classification(self):
data = Table("iris")
n_classes = len(data.domain.class_var.values)
res = CrossValidation(store_data=True)(data, [NaiveBayesLearner()])
table = res.get_augmented_data(['Naive Bayes'])
self.assertEqual(len(table), len(data))
self.assertEqual(len(table.domain.attributes),
len(data.domain.attributes))
self.assertEqual(len(table.domain.class_vars),
len(data.domain.class_vars))
# +1 for class, +n_classes for probabilities, +1 for fold
self.assertEqual(len(table.domain.metas),
len(data.domain.metas) + 1 + n_classes + 1)
self.assertEqual(table.domain.metas[len(data.domain.metas)].values,
data.domain.class_var.values)
res = CrossValidation(store_data=True)(
data, [NaiveBayesLearner(), MajorityLearner()])
table = res.get_augmented_data(['Naive Bayes', 'Majority'])
self.assertEqual(len(table), len(data))
self.assertEqual(len(table.domain.attributes),
len(data.domain.attributes))
self.assertEqual(len(table.domain.class_vars),
len(data.domain.class_vars))
self.assertEqual(len(table.domain.metas),
len(data.domain.metas) + 2 * (n_classes + 1) + 1)
self.assertEqual(table.domain.metas[len(data.domain.metas)].values,
data.domain.class_var.values)
self.assertEqual(table.domain.metas[len(data.domain.metas) + 1].values,
data.domain.class_var.values)
def test_augmented_data_classification(self):
data = Table("iris")
n_classes = len(data.domain.class_var.values)
res = CrossValidation(data, [NaiveBayesLearner()], store_data=True)
table = res.get_augmented_data(['Naive Bayes'])
self.assertEqual(len(table), len(data))
self.assertEqual(len(table.domain.attributes), len(data.domain.attributes))
self.assertEqual(len(table.domain.class_vars), len(data.domain.class_vars))
# +1 for class, +n_classes for probabilities, +1 for fold
self.assertEqual(
len(table.domain.metas), len(data.domain.metas) + 1 + n_classes + 1)
self.assertEqual(
table.domain.metas[len(data.domain.metas)].values, data.domain.class_var.values)
res = CrossValidation(data, [NaiveBayesLearner(), MajorityLearner()], store_data=True)
table = res.get_augmented_data(['Naive Bayes', 'Majority'])
self.assertEqual(len(table), len(data))
self.assertEqual(len(table.domain.attributes), len(data.domain.attributes))
self.assertEqual(len(table.domain.class_vars), len(data.domain.class_vars))
self.assertEqual(
len(table.domain.metas), len(data.domain.metas) + 2*(n_classes+1) + 1)
self.assertEqual(
table.domain.metas[len(data.domain.metas)].values, data.domain.class_var.values)
self.assertEqual(
table.domain.metas[len(data.domain.metas)+1].values, data.domain.class_var.values)
def test_augmented_data_regression(self):
data = Table("housing")
res = CrossValidation(data, [LinearRegressionLearner(), ], store_data=True)
table = res.get_augmented_data(['Linear Regression'])
self.assertEqual(len(table), len(data))
self.assertEqual(len(table.domain.attributes), len(data.domain.attributes))
self.assertEqual(len(table.domain.class_vars), len(data.domain.class_vars))
# +1 for class, +1 for fold
self.assertEqual(len(table.domain.metas), len(data.domain.metas) + 1 + 1)
res = CrossValidation(data, [LinearRegressionLearner(), MeanLearner()], store_data=True)
table = res.get_augmented_data(['Linear Regression', 'Mean Learner'])
self.assertEqual(len(table), len(data))
self.assertEqual(len(table.domain.attributes), len(data.domain.attributes))
self.assertEqual(len(table.domain.class_vars), len(data.domain.class_vars))
# +2 for class, +1 for fold
self.assertEqual(len(table.domain.metas), len(data.domain.metas) + 2 + 1)
