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Trained random forest models should have a .plot_feature_importances() method #457

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Aylr opened this issue Dec 19, 2017 · 0 comments
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@Aylr
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Aylr commented Dec 19, 2017

While this would benefit from #446 it could be done with a bit of hacky logic as an MVP

GWT

  • Given I am a user that has a trained random forest model

  • When I call the method trained_rf.plot_feature_importances()

  • Then I should see the feature importance plot shown during training.

  • Given I am a user that has a trained model of any other type

  • When I call the method trained_foo.plot_feature_importances()

  • Then I should see a warning or error message saying that this is only for random forest models

Notes

  • The current implentation of plot_rf_features_from_tsm() requires the x_train data. This isn't something we want to store in a serialized model for PHI, data security and performance reasons. Therefore, this will require some thought and investigation.
  • Some possible solutions:
    • Generate the plot and serialize it somehow during training as part of the TrainedSupervisedModel
    • ???
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