Transformers, new features, transfer learning#424
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stewarthe6 wants to merge 44 commits into1.8.0from
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…scaler_unit_variance
…ault true and default false lists
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
…e log scale features
…ndicator' flag because that changed the number of features and crashed.
…rming using SklearnPipelineWrapper
…g/AMPL into feat_scaled_rdkit_mordred
…e to transformers_x
…model, if transformers are saved and loaded correctly, and if transform_dataset_key_config is saved correctly
…r want to set that manually. Instead added a check when saving metadata to see if the parameters object has that attribute
…well as infill nan or extremely large values
Codecov Report✅ All modified and coverable lines are covered by tests. @@ Coverage Diff @@
## 1.8.0 #424 +/- ##
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+ Coverage 40.51% 41.65% +1.14%
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Files 50 51 +1
Lines 13518 13729 +211
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+ Hits 5477 5719 +242
+ Misses 8041 8010 -31
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... and 2 files with indirect coverage changes 🚀 New features to boost your workflow:
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…r molecular weight
… colliding split_uuids
…re_transformers when transformers is None. This does not test the pipeline with no transformers, just that the function returns correctly
- Tests that the heavyatom_col paramter is used correctly and cases when there is no heavyatom_col. - Tests that the NotImplementedError is raised correctly when there is no feature count or if there is no way to featurize data. - Tests that the Identity features transforms are returned correctly. And that an error is raised if an unrecognized feature transform is used.
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This is a large pull request with 3 new features.