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[ML] Add new include flag to GET inference/<model_id> API for model training metadata (#61922)
Adds new flag include to the get trained models API The flag initially has two valid values: definition, total_feature_importance. Consequently, the old include_model_definition flag is now deprecated. When total_feature_importance is included, the total_feature_importance field is included in the model metadata object. Including definition is the same as previously setting include_model_definition=true.
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29 changed files with 820 additions and 163 deletions
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@ -22,26 +22,28 @@ IDs, or the special wildcard `_all` to get all trained models.
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--------------------------------------------------
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include-tagged::{doc-tests-file}[{api}-request]
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--------------------------------------------------
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<1> Constructing a new GET request referencing an existing Trained Model
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<1> Constructing a new GET request referencing an existing trained model
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<2> Set the paging parameters
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<3> Indicate if the complete model definition should be included
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<4> Should the definition be fully decompressed on GET
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<5> Allow empty response if no Trained Models match the provided ID patterns.
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If false, an error will be thrown if no Trained Models match the
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<4> Indicate if the total feature importance for the features used in training
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should be included in the model `metadata` field.
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<5> Should the definition be fully decompressed on GET
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<6> Allow empty response if no trained models match the provided ID patterns.
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If false, an error will be thrown if no trained models match the
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ID patterns.
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<6> An optional list of tags used to narrow the model search. A Trained Model
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<7> An optional list of tags used to narrow the model search. A trained model
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can have many tags or none. The trained models in the response will
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contain all the provided tags.
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<7> Optional boolean value indicating if certain fields should be removed on
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retrieval. This is useful for getting the trained model in a format that
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can then be put into another cluster.
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<8> Optional boolean value for requesting the trained model in a format that can
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then be put into another cluster. Certain fields that can only be set when
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the model is imported are removed.
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include::../execution.asciidoc[]
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[id="{upid}-{api}-response"]
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==== Response
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The returned +{response}+ contains the requested Trained Model.
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The returned +{response}+ contains the requested trained model.
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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