Package co.elastic.clients.elasticsearch.ml

Class DataframeAnalysisRegression

java.lang.Object

co.elastic.clients.elasticsearch.ml.DataframeAnalysisBase

co.elastic.clients.elasticsearch.ml.DataframeAnalysisRegression

All Implemented Interfaces:

DataframeAnalysisVariant, JsonpSerializable, UnionVariant

@JsonpDeserializable
public final class DataframeAnalysisRegression
extends DataframeAnalysisBase
implements DataframeAnalysisVariant

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	DataframeAnalysisRegression.Builder	Builder for DataframeAnalysisRegression.

Nested classes/interfaces inherited from class co.elastic.clients.elasticsearch.ml.DataframeAnalysisBase

DataframeAnalysisBase.AbstractBuilder<BuilderT extends DataframeAnalysisBase.AbstractBuilder<BuilderT>>

Field Summary

Fields

Modifier and Type	Field	Description
static JsonpDeserializer<DataframeAnalysisRegression>	_DESERIALIZER	Json deserializer for DataframeAnalysisRegression

Constructor Summary

Constructors

Constructor	Description
DataframeAnalysisRegression(DataframeAnalysisRegression.Builder builder)
DataframeAnalysisRegression(java.util.function.Function<DataframeAnalysisRegression.Builder,DataframeAnalysisRegression.Builder> fn)

Method Summary

Modifier and Type	Method	Description
java.lang.String	_variantType()	DataframeAnalysis variant type
java.lang.String	lossFunction()	The loss function used during regression.
java.lang.Double	lossFunctionParameter()	A positive number that is used as a parameter to the loss_function.
protected void	serializeInternal(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper)
protected static void	setupDataframeAnalysisRegressionDeserializer(DelegatingDeserializer<DataframeAnalysisRegression.Builder> op)

Methods inherited from class co.elastic.clients.elasticsearch.ml.DataframeAnalysisBase

alpha, dependentVariable, downsampleFactor, earlyStoppingEnabled, eta, etaGrowthRatePerTree, featureBagFraction, featureProcessors, gamma, lambda, maxOptimizationRoundsPerHyperparameter, maxTrees, numTopFeatureImportanceValues, predictionFieldName, randomizeSeed, serialize, setupDataframeAnalysisBaseDeserializer, softTreeDepthLimit, softTreeDepthTolerance, trainingPercent

Methods inherited from class java.lang.Object

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

Methods inherited from interface co.elastic.clients.elasticsearch.ml.DataframeAnalysisVariant

_toDataframeAnalysis

Field Details

_DESERIALIZER

public static final JsonpDeserializer<DataframeAnalysisRegression> _DESERIALIZER

Json deserializer for DataframeAnalysisRegression

Constructor Details

DataframeAnalysisRegression

public DataframeAnalysisRegression(DataframeAnalysisRegression.Builder builder)

DataframeAnalysisRegression

public DataframeAnalysisRegression(java.util.function.Function<DataframeAnalysisRegression.Builder,DataframeAnalysisRegression.Builder> fn)

Method Details

_variantType

public java.lang.String _variantType()

DataframeAnalysis variant type

Specified by:

_variantType in interface UnionVariant

lossFunction

@Nullable
public java.lang.String lossFunction()

The loss function used during regression. Available options are mse (mean squared error), msle (mean squared logarithmic error), huber (Pseudo-Huber loss).

API name: loss_function

lossFunctionParameter

@Nullable
public java.lang.Double lossFunctionParameter()

A positive number that is used as a parameter to the loss_function.

API name: loss_function_parameter

serializeInternal

protected void serializeInternal(jakarta.json.stream.JsonGenerator generator,
JsonpMapper mapper)

Overrides:

serializeInternal in class DataframeAnalysisBase

setupDataframeAnalysisRegressionDeserializer

protected static void setupDataframeAnalysisRegressionDeserializer(DelegatingDeserializer<DataframeAnalysisRegression.Builder> op)