75 lines
2.7 KiB
Plaintext
75 lines
2.7 KiB
Plaintext
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[role="xpack"]
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[testenv="basic"]
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[[search-aggregations-pipeline-inference-bucket-aggregation]]
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=== Inference Bucket Aggregation
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A parent pipeline aggregation which loads a pre-trained model and performs inference on the
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collated result field from the parent bucket aggregation.
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[[inference-bucket-agg-syntax]]
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==== Syntax
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A `inference` aggregation looks like this in isolation:
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[source,js]
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--------------------------------------------------
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{
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"inference": {
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"model_id": "a_model_for_inference", <1>
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"inference_config": { <2>
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"regression_config": {
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"num_top_feature_importance_values": 2
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}
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},
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"buckets_path": {
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"avg_cost": "avg_agg", <3>
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"max_cost": "max_agg"
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}
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}
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}
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--------------------------------------------------
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// NOTCONSOLE
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<1> The ID of model to use.
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<2> The optional inference config which overrides the model's default settings
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<3> Map the value of `avg_agg` to the model's input field `avg_cost`
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[[inference-bucket-params]]
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.`inference` Parameters
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[options="header"]
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|===
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|Parameter Name |Description |Required |Default Value
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| `model_id` | The ID of the model to load and infer against | Required | -
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| `inference_config` | Contains the inference type and its options. There are two types: <<inference-agg-regression-opt,`regression`>> and <<inference-agg-classification-opt,`classification`>> | Optional | -
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| `buckets_path` | Defines the paths to the input aggregations and maps the aggregation names to the field names expected by the model.
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See <<buckets-path-syntax>> for more details | Required | -
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|===
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==== Configuration options for {infer} models
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The `inference_config` setting is optional and usaully isn't required as the pre-trained models come equipped with sensible defaults.
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In the context of aggregations some options can overridden for each of the 2 types of model.
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[discrete]
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[[inference-agg-regression-opt]]
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===== Configuration options for {regression} models
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`num_top_feature_importance_values`::
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(Optional, integer)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-regression-num-top-feature-importance-values]
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[discrete]
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[[inference-agg-classification-opt]]
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===== Configuration options for {classification} models
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`num_top_classes`::
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(Optional, integer)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-classification-num-top-classes]
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`num_top_feature_importance_values`::
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(Optional, integer)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-classification-num-top-feature-importance-values]
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`prediction_field_type`::
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(Optional, string)
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include::{es-repo-dir}/ml/ml-shared.asciidoc[tag=inference-config-classification-prediction-field-type]
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