Feature sklearn transformer #396
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…scaler_unit_variance
…ault true and default false lists
Codecov ReportAttention: Patch coverage is
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## 1.7.0 #396 +/- ##
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+ Coverage 34.54% 35.01% +0.46%
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Lines 13497 13529 +32
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+ Hits 4663 4737 +74
+ Misses 8834 8792 -42
... and 6 files with indirect coverage changes 🚀 New features to boost your workflow:
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Ipc should not be changed to AvgIpc like this because it would break all rdkit_raw models.
…th RobustScaler and PowerTransformer. Updated documentation in related sections. Added functions to ModelFileReader to read out transformer specific parameters. Changed models that test RobustScaler and PowerTransformer to use RF to speed up the training
…default function for all sklearn parameters
… it more generalizeable. Fixed tests. Fixed bug where the imputer_strategy parameter was not used
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This implements two transformers from sklearn, RobustScaler and PowerTransformer, that can be used for feature transformations instead of the default NormalizationTransformerMissingData.
A SimpleImputer is used before the RobustScaler and PowerTransformer to fill in any nan values. Default method is 'mean', but can be changed to 'most_frequent' and 'median'. The keep_empty_features parameter is always set to true, and those features will be filled with 0s.