def test_variance_drop_all(self):
data, label = get_data_label(load_boston())
method = SelectionMethod.Variance(threshold=100000)
selector = Selective(method)
try:
selector.fit(data)
selector.transform(data)
except ValueError:
pass
def test_variance_zero_threshold(self):
data, label = get_data_label(load_boston())
method = SelectionMethod.Variance(threshold=0)
selector = Selective(method)
selector.fit(data)
subset = selector.transform(data)
# Reduced columns
self.assertEqual(data.shape[1], 13)
self.assertEqual(subset.shape[1], 13)
def test_variance_drop_target(self):
data, label = get_data_label(load_boston())
method = SelectionMethod.Variance(threshold=85)
selector = Selective(method)
selector.fit(data)
subset = selector.transform(data)
# Reduced columns
self.assertEqual(data.shape[1], 13)
self.assertEqual(subset.shape[1], 4)
self.assertListEqual(list(subset.columns), ['ZN', 'AGE', 'TAX', 'B'])
def test_variance_lt1_fit_trans(self):
data, label = get_data_label(load_boston())
method = SelectionMethod.Variance(threshold=1.0)
selector = Selective(method)
subset = selector.fit_transform(data)
# Reduced columns
self.assertEqual(data.shape[1], 13)
self.assertEqual(subset.shape[1], 10)
self.assertListEqual(list(subset.columns), [
'CRIM', 'ZN', 'INDUS', 'AGE', 'DIS', 'RAD', 'TAX', 'PTRATIO', 'B',
'LSTAT'
])