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