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Introduce a way to extract intermediate outputs from a Pipeline without having to rebuild it and refit it.
The functionality should be something along this lines:
primitives = ['a', 'b', 'c', 'd'] pipeline = MLPipeline(['a', 'b', 'c', 'd']) pipeline.fit(train_X, train_y) output_of_b = pipeline.predict(train_X, output_='b')
The text was updated successfully, but these errors were encountered:
Merge pull request #58 from HDI-Project/issue_48_dynamic_error_thresh…
dd5d858
…olding Issue 48 dynamic error thresholding
csala
Successfully merging a pull request may close this issue.
Introduce a way to extract intermediate outputs from a Pipeline without having to rebuild it and refit it.
The functionality should be something along this lines:
The text was updated successfully, but these errors were encountered: