OpenSearch/docs/reference/ingest/processors/inference.asciidoc

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[role="xpack"]
[testenv="basic"]
[[inference-processor]]
=== {infer-cap} Processor
Uses a pre-trained {dfanalytics} model to infer against the data that is being
ingested in the pipeline.
[[inference-options]]
.{infer-cap} Options
[options="header"]
|======
| Name | Required | Default | Description
| `model_id` | yes | - | (String) The ID of the model to load and infer against.
| `target_field` | no | `ml.inference.<processor_tag>` | (String) Field added to incoming documents to contain results objects.
| `field_mappings` | yes | - | (Object) Maps the document field names to the known field names of the model.
| `inference_config` | yes | - | (Object) Contains the inference type and its options. There are two types: <<inference-processor-regression-opt,`regression`>> and <<inference-processor-classification-opt,`classification`>>.
include::common-options.asciidoc[]
|======
[source,js]
--------------------------------------------------
{
"inference": {
"model_id": "flight_delay_regression-1571767128603",
"target_field": "FlightDelayMin_prediction_infer",
"field_mappings": {},
"inference_config": { "regression": {} }
}
}
--------------------------------------------------
// NOTCONSOLE
[discrete]
[[inference-processor-regression-opt]]
==== {regression-cap} configuration options
`results_field`::
(Optional, string)
Specifies the field to which the inference prediction is written. Defaults to
`predicted_value`.
`num_top_feature_importance_values`::::
(Optional, integer)
Specifies the maximum number of
{ml-docs}/dfa-regression.html#dfa-regression-feature-importance[feature
importance] values per document. By default, it is zero and no feature importance
calculation occurs.
[discrete]
[[inference-processor-classification-opt]]
==== {classification-cap} configuration options
`results_field`::
(Optional, string)
The field that is added to incoming documents to contain the inference prediction. Defaults to
`predicted_value`.
`num_top_classes`::
(Optional, integer)
Specifies the number of top class predictions to return. Defaults to 0.
`top_classes_results_field`::
(Optional, string)
Specifies the field to which the top classes are written. Defaults to
`top_classes`.
`num_top_feature_importance_values`::::
(Optional, integer)
Specifies the maximum number of
{ml-docs}/dfa-classification.html#dfa-classification-feature-importance[feature
importance] values per document. By default, it is zero and no feature importance
calculation occurs.
[discrete]
[[inference-processor-config-example]]
==== `inference_config` examples
[source,js]
--------------------------------------------------
{
"inference_config": {
"regression": {
"results_field": "my_regression"
}
}
}
--------------------------------------------------
// NOTCONSOLE
This configuration specifies a `regression` inference and the results are
written to the `my_regression` field contained in the `target_field` results
object.
[source,js]
--------------------------------------------------
{
"inference_config": {
"classification": {
"num_top_classes": 2,
"results_field": "prediction",
"top_classes_results_field": "probabilities"
}
}
}
--------------------------------------------------
// NOTCONSOLE
This configuration specifies a `classification` inference. The number of
categories for which the predicted probabilities are reported is 2
(`num_top_classes`). The result is written to the `prediction` field and the top
classes to the `probabilities` field. Both fields are contained in the
`target_field` results object.