Package co.elastic.clients.elasticsearch.ml

Class DataframeAnalysisRegression.Builder

java.lang.Object

co.elastic.clients.elasticsearch.ml.DataframeAnalysisBase.AbstractBuilder<DataframeAnalysisRegression.Builder>

co.elastic.clients.elasticsearch.ml.DataframeAnalysisRegression.Builder

All Implemented Interfaces:

ObjectBuilder<DataframeAnalysisRegression>

Enclosing class:

DataframeAnalysisRegression

public static class DataframeAnalysisRegression.Builder
extends DataframeAnalysisBase.AbstractBuilder<DataframeAnalysisRegression.Builder>
implements ObjectBuilder<DataframeAnalysisRegression>

Builder for DataframeAnalysisRegression.

Constructor Summary

Constructors

Constructor	Description
Builder()

Method Summary

Modifier and Type	Method	Description
DataframeAnalysisRegression	build()	Builds a DataframeAnalysisRegression.
DataframeAnalysisRegression.Builder	lossFunction(java.lang.String value)	The loss function used during regression.
DataframeAnalysisRegression.Builder	lossFunctionParameter(java.lang.Double value)	A positive number that is used as a parameter to the loss_function.
protected DataframeAnalysisRegression.Builder	self()

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

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

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

lossFunction

public DataframeAnalysisRegression.Builder lossFunction(@Nullable
java.lang.String value)

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

public DataframeAnalysisRegression.Builder lossFunctionParameter(@Nullable
java.lang.Double value)

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

API name: loss_function_parameter

self

protected DataframeAnalysisRegression.Builder self()

Specified by:

self in class DataframeAnalysisBase.AbstractBuilder<DataframeAnalysisRegression.Builder>

build

public DataframeAnalysisRegression build()

Builds a DataframeAnalysisRegression.

Specified by:

build in interface ObjectBuilder<DataframeAnalysisRegression>

Throws:

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