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Add get_feature_contributions method to Pipeline #186
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ganik
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Jul 15, 2019
ganik
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Jul 15, 2019
ganik
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Jul 15, 2019
ganik
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Jul 15, 2019
ganik
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Jul 15, 2019
ganik
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Jul 15, 2019
najeeb-kazmi
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ganik
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Jul 18, 2019
ganik
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Jul 18, 2019
ganik
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Jul 18, 2019
ganik
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Jul 18, 2019
ganik
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Jul 18, 2019
ganik
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Jul 18, 2019
* Save the model file when pickling a NimbusML Pipeline. * Add version to the pickled Pipeline. * Add the steps attribute to a pickled Pipeline instance. * Add extra unit test for pickled nimbusml pipelines. * Add export_version to pickled base_pipeline_items. Remove unnecessary export_version attribute from an unpickled Pipeline.
* Remove stored references to X and y in BasePredictor. * Remove unnecessary scikit-learn import.
ganik
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Jul 19, 2019
ganik
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Jul 19, 2019
| "Restore a pickled object." | ||
| for k, v in state.items(): | ||
| if k not in {'modelbytes', 'type'}: | ||
| if k not in {'modelbytes', 'type', 'export_version'}: |
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can u rebase ? this change should be in master already
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I did, but the commit history in this branch got screwed up while fixing conflicts. This (and other changes) aren't actually in this PR.
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Closing this and replacing with PR #196 |
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Fix #91
Adds a
get_feature_contributions()method toPipeline, which works similarly topredict()but adds atransforms_featurecontributioncalculationtransformernode after thetransforms_datasetscorernode in the graph that gets executed.Adds a
get_feature_contributions()method toBasePredictorso that models trained outside of aPipelinealso return feature contributions.Adds an example of how to use this.
Adds a test to check that an unpickled model can calculate feature contributions.
Adds a test to check that a model loaded from zip can calculate feature contributions.