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@@ 41-57 (lines=17) @@
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| 38 |
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self.assertEqual(train_dev_test_split(self.data_split, target='Col2', |
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dev_size=0.5, test_size=0)[i].shape, expected_results[i]) |
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| 41 |
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def test_train_dev_test_split_series(self): |
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# Test the propper splitting in train, dev and test sets |
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expected_results = [(6, 5), (2, 5), (2, 5), (6,), (2,), (2,)] |
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for i, _ in enumerate(expected_results): |
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self.assertEqual(train_dev_test_split(self.data_split, target=self.data_target, |
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dev_size=0.2, test_size=0.2)[i].shape, expected_results[i]) |
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expected_results = [(8, 5), (2, 5), (8,), (2,)] |
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for i, _ in enumerate(expected_results): |
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self.assertEqual(train_dev_test_split(self.data_split, target=self.data_target, |
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dev_size=0, test_size=0.2)[i].shape, expected_results[i]) |
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expected_results = [(5, 5), (5, 5), (5,), (5,)] |
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for i, _ in enumerate(expected_results): |
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self.assertEqual(train_dev_test_split(self.data_split, target=self.data_target, |
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dev_size=0.5, test_size=0)[i].shape, expected_results[i]) |
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@@ 23-38 (lines=16) @@
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columns=['Col1', 'Col2', 'Col3', 'Col4', 'Col5']) |
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cls.data_target = pd.Series([1, 0, 1, 0, 0, 1, 1, 0, 1, 1]) |
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def test_train_dev_test_split_col(self): |
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# Test the propper splitting in train, dev and test sets |
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expected_results = [(8, 4), (1, 4), (1, 4), (8,), (1,), (1,)] |
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for i, _ in enumerate(expected_results): |
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self.assertEqual(train_dev_test_split(self.data_split, 'Col2', |
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random_state=1234)[i].shape, expected_results[i]) |
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expected_results = [(8, 4), (2, 4), (8,), (2,)] |
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for i, _ in enumerate(expected_results): |
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self.assertEqual(train_dev_test_split(self.data_split, target='Col2', |
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dev_size=0, test_size=0.2)[i].shape, expected_results[i]) |
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expected_results = [(5, 4), (5, 4), (5,), (5,)] |
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for i, _ in enumerate(expected_results): |
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self.assertEqual(train_dev_test_split(self.data_split, target='Col2', |
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dev_size=0.5, test_size=0)[i].shape, expected_results[i]) |
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| 41 |
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def test_train_dev_test_split_series(self): |
akanz1 /
klib
