Fix regression algorithms to give correct output dimensions #1335
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@@ Coverage Diff @@
## development #1335 +/- ##
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+ Coverage 87.90% 87.97% +0.07%
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Files 140 140
Lines 10938 10977 +39
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+ Hits 9615 9657 +42
+ Misses 1323 1320 -3
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mfeurer
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Dec 8, 2021
mfeurer
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Dec 10, 2021
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eddiebergman
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Jan 25, 2022
* Added ignored_warnings file * Use ignored_warnings file * Test regressors with 1d, 1d as 2d and 2d targets * Flake'd * Fix broken relative imports to ignore_warnings * Removed print and updated parameter type for tests * Type import fix
Merged
eddiebergman
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Aug 18, 2022
* Added ignored_warnings file * Use ignored_warnings file * Test regressors with 1d, 1d as 2d and 2d targets * Flake'd * Fix broken relative imports to ignore_warnings * Removed print and updated parameter type for tests * Type import fix
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This PR addresses issue #1297 in which some regressors gave the wrong output dimensions. This was due to the use of
StandardScaleron the target column(s)y. The main source of the issue was due to the regressors not being updated one multi-output regression was considered.Issues
[0,0,0] -> [[0], [0], [0]][[1,1], [1,1]] -> [[1], [1], [1], [1]]scaler.inverse_transform([1,1,1]) -> [[1], [1], [1]].Created tests for all regression algorithms (classifiers do not use standard scalers). These test the algorithms with 3 different kinds of target shapes. These tests also check that the output shape is correct, where
(n,1)is flattened back out to(n,).(n,) -> (n,)(n,1) -> (n,)(n,m) -> (n,m)This PR also consolidates all the ignored warnings into one file and provides a context manager to be used in tests if we want to ignore warnings.