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Feature Importance via attention weights
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@jrzaurin jrzaurin released this 21 Jul 07:37
· 193 commits to master since this release
v1.3.0
4af577a
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Learn about vigilant mode.
  • Added a new functionality to access feature importance via attention weights for all DL models for Tabular data except for the TabPerceiver. This functionality is accessed via the feature_importance attribute in the trainer (computed during training with a sample of observations) and at predict time via de explain method.
  • Fix all restore weights capabilities in all forms of training. Such capabilities are present in two callbacks, the EarlyStopping and the ModelCheckpoint Callbacks. Prior to this release there was a bug and the weights were not restored.
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