119 lines
3.8 KiB
Plaintext
119 lines
3.8 KiB
Plaintext
[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_map` | yes | - | (Object) Maps the document field names to the known field names of the model. This mapping takes precedence over any default mappings provided in the model configuration.
|
|
| `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_map": {},
|
|
"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.
|