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[ML] Add new feature_processing field to Data frame analytics config #59327

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benwtrent opened this issue Jul 9, 2020 · 1 comment · Fixed by #60528
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[ML] Add new feature_processing field to Data frame analytics config #59327

benwtrent opened this issue Jul 9, 2020 · 1 comment · Fixed by #60528
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>enhancement :ml Machine learning

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@benwtrent
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benwtrent commented Jul 9, 2020

Data frame analytics jobs should handle a new configuration field called feature_processing.

This field will be an array of PreProcessor objects.

Requirements:

  • feature_processing array gets serialized as a parameter to the analysis native process
  • include/exclude works with custom fields.
    • excluded fields can STILL be used in a feature_processing processor.
    • a feature_processing processed field cannot be excluded.
  • Before data is extracted and sent to the native process, the data needs to be pushed through the feature_processing processors
@benwtrent benwtrent added >enhancement :ml Machine learning labels Jul 9, 2020
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Pinging @elastic/ml-core (:ml)

benwtrent added a commit that referenced this issue Aug 14, 2020
feature_processors allow users to create custom features from
individual document fields.

These `feature_processors` are the same object as the trained model's pre_processors. 

They are passed to the native process and the native process then appends them to the
pre_processor array in the inference model.

closes #59327
benwtrent added a commit to benwtrent/elasticsearch that referenced this issue Aug 14, 2020
…tic#60528)

feature_processors allow users to create custom features from
individual document fields.

These `feature_processors` are the same object as the trained model's pre_processors.

They are passed to the native process and the native process then appends them to the
pre_processor array in the inference model.

closes elastic#59327
benwtrent added a commit that referenced this issue Aug 14, 2020
…) (#61148)

feature_processors allow users to create custom features from
individual document fields.

These `feature_processors` are the same object as the trained model's pre_processors.

They are passed to the native process and the native process then appends them to the
pre_processor array in the inference model.

closes #59327
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Labels
>enhancement :ml Machine learning
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