Fix mrmr working with categoricals #1311
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## master #1311 +/- ##
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- Coverage 88.20% 56.03% -32.17%
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Files 186 197 +11
Lines 11807 12126 +319
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- Hits 10414 6795 -3619
- Misses 1393 5331 +3938
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🚀 Deployed on https://deploy-preview-1311--etna-docs.netlify.app |
| @@ -82,6 +82,14 @@ def mrmr( | |||
| redundancy_table = pd.DataFrame(np.inf, index=all_features, columns=all_features) | |||
| top_k = min(top_k, len(all_features)) | |||
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| # can't compute correlation of categorical column with the others | |||
| cat_cols = regressors.dtypes[regressors.dtypes == "category"].index | |||
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Won't it be easier to cast all regressors to float?
| try: | ||
| regressors[cat_col] = regressors[cat_col].astype(float) | ||
| except ValueError: | ||
| raise ValueError(f"{cat_col} column cannot be cast to float type! Please, use encoders.") |
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We should test this error.
| @@ -32,6 +33,12 @@ def df_with_regressors() -> Dict[str, pd.DataFrame]: | |||
| regressor = df_regressors_useless[df_regressors_useless["segment"] == segment]["target"].values | |||
| df_exog[f"regressor_useless_{i}"] = regressor | |||
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| # useless categorical regressor | |||
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regressor -> regressors?
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| @pytest.mark.parametrize("fast_redundancy", [True, False]) | ||
| def test_mrmr_with_categorical_regressor(df_with_regressors, fast_redundancy): |
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test_mrmr_with_categorical_regressor -> test_mrmr_with_castable_categorical_regressor?
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Proposed Changes
Closing issues
closes #1310