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[DOCS] Add feature_importance_baseline to get trained model API (#63279)

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Co-authored-by: Benjamin Trent <ben.w.trent@gmail.com>
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Lisa Cawley 2020-10-06 07:56:55 -07:00 • committed by GitHub
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18
docs/java-rest/high-level/ml/get-trained-models.asciidoc
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@ -22,19 +22,21 @@ IDs, or the special wildcard `_all` to get all trained models.
--------------------------------------------------
include-tagged::{doc-tests-file}[{api}-request]
--------------------------------------------------
<1> Constructing a new GET request referencing an existing trained model
<2> Set the paging parameters
<3> Indicate if the complete model definition should be included
<1> Constructing a new GET request referencing an existing trained model.
<2> Set the paging parameters.
<3> Indicate if the complete model definition should be included.
<4> Indicate if the total feature importance for the features used in training
should be included in the model `metadata` field.
<5> Should the definition be fully decompressed on GET
<6> Allow empty response if no trained models match the provided ID patterns.
should is included in the metadata.
<5> Indicate if the feature importance baselines that were used in training are
included in the metadata.
<6> Should the definition be fully decompressed on GET.
<7> Allow empty response if no trained models match the provided ID patterns.
If false, an error will be thrown if no trained models match the
ID patterns.
<7> An optional list of tags used to narrow the model search. A trained model
<8> An optional list of tags used to narrow the model search. A trained model
can have many tags or none. The trained models in the response will
contain all the provided tags.
<8> Optional boolean value for requesting the trained model in a format that can
<9> Optional boolean value for requesting the trained model in a format that can
then be put into another cluster. Certain fields that can only be set when
the model is imported are removed.