[DOCS] Adds an example of preprocessing actions to the PUT DFA API docs (#49831)
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István Zoltán Szabó
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@ -102,11 +102,11 @@ single number. For example, in case of age ranges, you can model the values as
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`analyzed_fields`::
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(Optional, object) Specify `includes` and/or `excludes` patterns to select
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which fields will be included in the analysis. If `analyzed_fields` is not set,
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only the relevant fields will be included. For example, all the numeric fields
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for {oldetection}. For the supported field types, see <<ml-put-dfanalytics-supported-fields>>.
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Also see the <<explain-dfanalytics>> which helps understand
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field selection.
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which fields will be included in the analysis. If `analyzed_fields` is not
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set, only the relevant fields will be included. For example, all the numeric
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fields for {oldetection}. For the supported field types, see
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<<ml-put-dfanalytics-supported-fields>>. Also see the <<explain-dfanalytics>>
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which helps understand field selection.
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`includes`:::
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(Optional, array) An array of strings that defines the fields that will be
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@ -142,8 +142,8 @@ single number. For example, in case of age ranges, you can model the values as
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that setting. For more information, see <<ml-settings>>.
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`source`::
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(object) The configuration of how to source the analysis data. It requires an `index`.
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Optionally, `query` and `_source` may be specified.
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(object) The configuration of how to source the analysis data. It requires an
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`index`. Optionally, `query` and `_source` may be specified.
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`index`:::
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(Required, string or array) Index or indices on which to perform the
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@ -163,12 +163,12 @@ single number. For example, in case of age ranges, you can model the values as
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cannot be included in the analysis.
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`includes`::::
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(array) An array of strings that defines the fields that will be included in
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the destination.
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(array) An array of strings that defines the fields that will be
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included in the destination.
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`excludes`::::
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(array) An array of strings that defines the fields that will be excluded
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from the destination.
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(array) An array of strings that defines the fields that will be
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excluded from the destination.
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`allow_lazy_start`::
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(Optional, boolean) Whether this job should be allowed to start when there
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@ -187,6 +187,79 @@ single number. For example, in case of age ranges, you can model the values as
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==== {api-examples-title}
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[[ml-put-dfanalytics-example-preprocess]]
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===== Preprocessing actions example
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The following example shows how to limit the scope of the analysis to certain
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fields, specify excluded fields in the destination index, and use a query to
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filter your data before analysis.
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[source,console]
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--------------------------------------------------
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PUT _ml/data_frame/analytics/model-flight-delays-pre
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{
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"source": {
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"index": [
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"kibana_sample_data_flights" <1>
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],
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"query": { <2>
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"range": {
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"DistanceKilometers": {
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"gt": 0
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}
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}
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},
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"_source": { <3>
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"includes": [],
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"excludes": [
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"FlightDelay",
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"FlightDelayType"
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]
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}
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},
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"dest": { <4>
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"index": "df-flight-delays",
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"results_field": "ml-results"
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},
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"analysis": {
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"regression": {
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"dependent_variable": "FlightDelayMin",
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"training_percent": 90
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}
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},
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"analyzed_fields": { <5>
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"includes": [],
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"excludes": [
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"FlightNum"
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]
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},
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"model_memory_limit": "100mb"
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}
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--------------------------------------------------
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// TEST[skip:setup kibana sample data]
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<1> The source index to analyze.
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<2> This query filters out entire documents that will not be present in the
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destination index.
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<3> The `_source` object defines fields in the dataset that will be included or
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excluded in the destination index. In this case, `includes` does not specify any
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fields, so the default behavior takes place: all the fields of the source index
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will included except the ones that are explicitly specified in `excludes`.
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<4> Defines the destination index that contains the results of the analysis and
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the fields of the source index specified in the `_source` object. Also defines
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the name of the `results_field`.
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<5> Specifies fields to be included in or excluded from the analysis. This does
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not affect whether the fields will be present in the destination index, only
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affects whether they are used in the analysis.
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In this example, we can see that all the fields of the source index are included
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in the destination index except `FlightDelay` and `FlightDelayType` because
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these are defined as excluded fields by the `excludes` parameter of the
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`_source` object. The `FlightNum` field is included in the destination index,
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however it is not included in the analysis because it is explicitly specified as
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excluded field by the `excludes` parameter of the `analyzed_fields` object.
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[[ml-put-dfanalytics-example-od]]
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===== {oldetection-cap} example
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