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[7.16][DOCS] Move trained model APIs out of dataframe analytics (#81315
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…) (#81324)
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lcawl authored Dec 3, 2021
1 parent 14e1f00 commit d68c756
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10 changes: 2 additions & 8 deletions docs/reference/ml/df-analytics/apis/index.asciidoc
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include::ml-df-analytics-apis.asciidoc[leveloffset=+1]
//CREATE
include::put-dfanalytics.asciidoc[leveloffset=+2]
include::put-trained-models-aliases.asciidoc[leveloffset=+2]
include::put-trained-models.asciidoc[leveloffset=+2]
//UPDATE
include::update-dfanalytics.asciidoc[leveloffset=+2]
//DELETE
include::delete-dfanalytics.asciidoc[leveloffset=+2]
include::delete-trained-models.asciidoc[leveloffset=+2]
include::delete-trained-models-aliases.asciidoc[leveloffset=+2]
//EVALUATE
include::evaluate-dfanalytics.asciidoc[leveloffset=+2]
//ESTIMATE_MEMORY_USAGE
include::explain-dfanalytics.asciidoc[leveloffset=+2]
//GET
include::get-dfanalytics.asciidoc[leveloffset=+2]
include::get-dfanalytics-stats.asciidoc[leveloffset=+2]
include::get-trained-models.asciidoc[leveloffset=+2]
include::get-trained-models-stats.asciidoc[leveloffset=+2]
//PREVIEW
include::preview-dfanalytics.asciidoc[leveloffset=+2]
//SET/START/STOP
include::start-dfanalytics.asciidoc[leveloffset=+2]
include::stop-dfanalytics.asciidoc[leveloffset=+2]
//UPDATE
include::update-dfanalytics.asciidoc[leveloffset=+2]
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Expand Up @@ -12,24 +12,4 @@ You can use the following APIs to perform {ml} {dfanalytics} activities.
* <<get-dfanalytics-stats,Get {dfanalytics-jobs} statistics>>
* <<start-dfanalytics,Start {dfanalytics-jobs}>>
* <<stop-dfanalytics,Stop {dfanalytics-jobs}>>
* <<evaluate-dfanalytics,Evaluate {dfanalytics}>>
* <<explain-dfanalytics,Explain {dfanalytics}>>


You can use the following APIs to perform {infer} operations.

* <<put-trained-models>>
* <<get-trained-models>>
* <<get-trained-models-stats>>
* <<delete-trained-models>>
* <<put-trained-models-aliases>>
* <<delete-trained-models-aliases>>

You can deploy a trained model to make predictions in an ingest pipeline or in
an aggregation. Refer to the following documentation to learn more.

* <<inference-processor,{infer-cap} processor>>
* <<search-aggregations-pipeline-inference-bucket-aggregation,{infer-cap} bucket aggregation>>


See also <<ml-apis>>.
* <<update-dfanalytics,Update {dfanalytics-jobs}>>
11 changes: 11 additions & 0 deletions docs/reference/ml/trained-models/apis/index.asciidoc
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@@ -0,0 +1,11 @@
include::ml-trained-models-apis.asciidoc[leveloffset=+1]
//CREATE
include::put-trained-models-aliases.asciidoc[leveloffset=+2]
include::put-trained-models.asciidoc[leveloffset=+2]
//DELETE
include::delete-trained-models-aliases.asciidoc[leveloffset=+2]
include::delete-trained-models.asciidoc[leveloffset=+2]
//GET
include::get-trained-models.asciidoc[leveloffset=+2]
include::get-trained-models-stats.asciidoc[leveloffset=+2]

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@@ -0,0 +1,18 @@
[role="xpack"]
[[ml-df-trained-models-apis]]
= {ml-cap} trained model APIs

You can use the following APIs to perform model management operations:

* <<put-trained-models>>
* <<put-trained-models-aliases>>
* <<delete-trained-models>>
* <<delete-trained-models-aliases>>
* <<get-trained-models>>
* <<get-trained-models-stats>>

You can deploy a trained model to make predictions in an ingest pipeline or in
an aggregation. Refer to the following documentation to learn more:

* <<search-aggregations-pipeline-inference-bucket-aggregation,{infer-cap} bucket aggregation>>
* <<inference-processor,{infer-cap} processor>>
1 change: 1 addition & 0 deletions docs/reference/rest-api/index.asciidoc
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Expand Up @@ -69,6 +69,7 @@ include::{es-repo-dir}/licensing/index.asciidoc[]
include::{xes-repo-dir}/rest-api/logstash/index.asciidoc[]
include::{es-repo-dir}/ml/anomaly-detection/apis/index.asciidoc[]
include::{es-repo-dir}/ml/df-analytics/apis/index.asciidoc[]
include::{es-repo-dir}/ml/trained-models/apis/index.asciidoc[]
include::{es-repo-dir}/migration/migration.asciidoc[]
include::{es-repo-dir}/shutdown/apis/shutdown-api.asciidoc[]
include::{es-repo-dir}/indices/apis/reload-analyzers.asciidoc[]
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