Package co.elastic.clients.elasticsearch.ml

Class TrainedModelConfig.Builder

java.lang.Object

co.elastic.clients.elasticsearch.ml.TrainedModelConfig.Builder

All Implemented Interfaces:

ObjectBuilder<TrainedModelConfig>

Enclosing class:

TrainedModelConfig

public static class TrainedModelConfig.Builder
extends java.lang.Object
implements ObjectBuilder<TrainedModelConfig>

Builder for TrainedModelConfig.

Constructor Summary

Constructors

Constructor	Description
Builder()

Method Summary

Modifier and Type	Method	Description
TrainedModelConfig.Builder	addTags(java.lang.String value)	Add a value to tags(List), creating the list if needed.
TrainedModelConfig	build()	Builds a TrainedModelConfig.
TrainedModelConfig.Builder	compressedDefinition(java.lang.String value)	API name: compressed_definition
TrainedModelConfig.Builder	createdBy(java.lang.String value)	Information on the creator of the trained model.
TrainedModelConfig.Builder	createTime(java.lang.String value)	The time when the trained model was created.
TrainedModelConfig.Builder	defaultFieldMap(java.util.Map<java.lang.String,java.lang.String> value)	Any field map described in the inference configuration takes precedence.
TrainedModelConfig.Builder	description(java.lang.String value)	The free-text description of the trained model.
TrainedModelConfig.Builder	estimatedHeapMemoryUsageBytes(java.lang.Integer value)	The estimated heap usage in bytes to keep the trained model in memory.
TrainedModelConfig.Builder	estimatedOperations(java.lang.Integer value)	The estimated number of operations to use the trained model.
TrainedModelConfig.Builder	inferenceConfig(InferenceConfig value)	The default configuration for inference.
TrainedModelConfig.Builder	inferenceConfig(java.util.function.Function<InferenceConfig.Builder,ObjectBuilder<InferenceConfig>> fn)	The default configuration for inference.
TrainedModelConfig.Builder	input(TrainedModelConfigInput value)	The input field names for the model definition.
TrainedModelConfig.Builder	input(java.util.function.Function<TrainedModelConfigInput.Builder,ObjectBuilder<TrainedModelConfigInput>> fn)	The input field names for the model definition.
TrainedModelConfig.Builder	licenseLevel(java.lang.String value)	The license level of the trained model.
TrainedModelConfig.Builder	metadata(TrainedModelConfigMetadata value)	An object containing metadata about the trained model.
TrainedModelConfig.Builder	metadata(java.util.function.Function<TrainedModelConfigMetadata.Builder,ObjectBuilder<TrainedModelConfigMetadata>> fn)	An object containing metadata about the trained model.
TrainedModelConfig.Builder	modelId(java.lang.String value)	Idetifier for the trained model.
TrainedModelConfig.Builder	putDefaultFieldMap(java.lang.String key, java.lang.String value)	Add a key/value to defaultFieldMap(Map), creating the map if needed.
TrainedModelConfig.Builder	tags(java.lang.String... value)	A comma delimited string of tags.
TrainedModelConfig.Builder	tags(java.util.List<java.lang.String> value)	A comma delimited string of tags.
TrainedModelConfig.Builder	version(java.lang.String value)	The Elasticsearch version number in which the trained model was created.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

Builder

public Builder()

Method Details

modelId

public TrainedModelConfig.Builder modelId(java.lang.String value)

Idetifier for the trained model.

API name: model_id

tags

public TrainedModelConfig.Builder tags(java.util.List<java.lang.String> value)

A comma delimited string of tags. A trained model can have many tags, or none.

API name: tags

tags

public TrainedModelConfig.Builder tags(java.lang.String... value)

A comma delimited string of tags. A trained model can have many tags, or none.

API name: tags

addTags

public TrainedModelConfig.Builder addTags(java.lang.String value)

Add a value to tags(List), creating the list if needed. 4

version

public TrainedModelConfig.Builder version(@Nullable
java.lang.String value)

The Elasticsearch version number in which the trained model was created.

API name: version

compressedDefinition

public TrainedModelConfig.Builder compressedDefinition(@Nullable
java.lang.String value)

API name: compressed_definition

createdBy

public TrainedModelConfig.Builder createdBy(@Nullable
java.lang.String value)

Information on the creator of the trained model.

API name: created_by

createTime

public TrainedModelConfig.Builder createTime(@Nullable
java.lang.String value)

The time when the trained model was created.

API name: create_time

defaultFieldMap

public TrainedModelConfig.Builder defaultFieldMap(@Nullable
java.util.Map<java.lang.String,java.lang.String> value)

Any field map described in the inference configuration takes precedence.

API name: default_field_map

putDefaultFieldMap

public TrainedModelConfig.Builder putDefaultFieldMap(java.lang.String key,
java.lang.String value)

Add a key/value to defaultFieldMap(Map), creating the map if needed.

description

public TrainedModelConfig.Builder description(@Nullable
java.lang.String value)

The free-text description of the trained model.

API name: description

estimatedHeapMemoryUsageBytes

public TrainedModelConfig.Builder estimatedHeapMemoryUsageBytes(@Nullable
java.lang.Integer value)

The estimated heap usage in bytes to keep the trained model in memory.

API name: estimated_heap_memory_usage_bytes

estimatedOperations

public TrainedModelConfig.Builder estimatedOperations(@Nullable
java.lang.Integer value)

The estimated number of operations to use the trained model.

API name: estimated_operations

inferenceConfig

public TrainedModelConfig.Builder inferenceConfig(InferenceConfig value)

The default configuration for inference. This can be either a regression or classification configuration. It must match the underlying definition.trained_model's target_type.

API name: inference_config

inferenceConfig

public TrainedModelConfig.Builder inferenceConfig(java.util.function.Function<InferenceConfig.Builder,ObjectBuilder<InferenceConfig>> fn)

The default configuration for inference. This can be either a regression or classification configuration. It must match the underlying definition.trained_model's target_type.

API name: inference_config

input

public TrainedModelConfig.Builder input(TrainedModelConfigInput value)

The input field names for the model definition.

API name: input

input

public TrainedModelConfig.Builder input(java.util.function.Function<TrainedModelConfigInput.Builder,ObjectBuilder<TrainedModelConfigInput>> fn)

The input field names for the model definition.

API name: input

licenseLevel

public TrainedModelConfig.Builder licenseLevel(@Nullable
java.lang.String value)

The license level of the trained model.

API name: license_level

metadata

public TrainedModelConfig.Builder metadata(@Nullable
TrainedModelConfigMetadata value)

An object containing metadata about the trained model. For example, models created by data frame analytics contain analysis_config and input objects.

API name: metadata

metadata

public TrainedModelConfig.Builder metadata(java.util.function.Function<TrainedModelConfigMetadata.Builder,ObjectBuilder<TrainedModelConfigMetadata>> fn)

An object containing metadata about the trained model. For example, models created by data frame analytics contain analysis_config and input objects.

API name: metadata

build

public TrainedModelConfig build()

Builds a TrainedModelConfig.

Specified by:

build in interface ObjectBuilder<TrainedModelConfig>

Throws:

java.lang.NullPointerException - if some of the required fields are null.