Package co.elastic.clients.elasticsearch.ml.evaluate_data_frame

Class DataframeRegressionSummary.Builder

java.lang.Object

co.elastic.clients.util.ObjectBuilderBase

co.elastic.clients.util.WithJsonObjectBuilderBase<DataframeRegressionSummary.Builder>

co.elastic.clients.elasticsearch.ml.evaluate_data_frame.DataframeRegressionSummary.Builder

All Implemented Interfaces:

WithJson<DataframeRegressionSummary.Builder>, ObjectBuilder<DataframeRegressionSummary>

Enclosing class:

DataframeRegressionSummary

public static class DataframeRegressionSummary.Builder
extends WithJsonObjectBuilderBase<DataframeRegressionSummary.Builder>
implements ObjectBuilder<DataframeRegressionSummary>

Builder for DataframeRegressionSummary.

Constructor Summary

Constructors

Constructor	Description
Builder()

Method Summary

Modifier and Type	Method	Description
DataframeRegressionSummary	build()	Builds a DataframeRegressionSummary.
final DataframeRegressionSummary.Builder	huber(DataframeEvaluationValue value)	Pseudo Huber loss function.
final DataframeRegressionSummary.Builder	huber(Function<DataframeEvaluationValue.Builder,ObjectBuilder<DataframeEvaluationValue>> fn)	Pseudo Huber loss function.
final DataframeRegressionSummary.Builder	mse(DataframeEvaluationValue value)	Average squared difference between the predicted values and the actual (ground truth) value.
final DataframeRegressionSummary.Builder	mse(Function<DataframeEvaluationValue.Builder,ObjectBuilder<DataframeEvaluationValue>> fn)	Average squared difference between the predicted values and the actual (ground truth) value.
final DataframeRegressionSummary.Builder	msle(DataframeEvaluationValue value)	Average squared difference between the logarithm of the predicted values and the logarithm of the actual (ground truth) value.
final DataframeRegressionSummary.Builder	msle(Function<DataframeEvaluationValue.Builder,ObjectBuilder<DataframeEvaluationValue>> fn)	Average squared difference between the logarithm of the predicted values and the logarithm of the actual (ground truth) value.
final DataframeRegressionSummary.Builder	rSquared(DataframeEvaluationValue value)	Proportion of the variance in the dependent variable that is predictable from the independent variables.
final DataframeRegressionSummary.Builder	rSquared(Function<DataframeEvaluationValue.Builder,ObjectBuilder<DataframeEvaluationValue>> fn)	Proportion of the variance in the dependent variable that is predictable from the independent variables.
protected DataframeRegressionSummary.Builder	self()

Methods inherited from class co.elastic.clients.util.WithJsonObjectBuilderBase

withJson

Methods inherited from class co.elastic.clients.util.ObjectBuilderBase

_checkSingleUse, _listAdd, _listAddAll, _mapPut, _mapPutAll

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.json.WithJson

withJson, withJson

Constructor Details

Builder

public Builder()

Method Details

huber

public final DataframeRegressionSummary.Builder huber(@Nullable
 DataframeEvaluationValue value)

Pseudo Huber loss function.

API name: huber

huber

public final DataframeRegressionSummary.Builder huber(Function<DataframeEvaluationValue.Builder,ObjectBuilder<DataframeEvaluationValue>> fn)

Pseudo Huber loss function.

API name: huber

mse

public final DataframeRegressionSummary.Builder mse(@Nullable
 DataframeEvaluationValue value)

Average squared difference between the predicted values and the actual (ground truth) value.

API name: mse

mse

public final DataframeRegressionSummary.Builder mse(Function<DataframeEvaluationValue.Builder,ObjectBuilder<DataframeEvaluationValue>> fn)

Average squared difference between the predicted values and the actual (ground truth) value.

API name: mse

msle

public final DataframeRegressionSummary.Builder msle(@Nullable
 DataframeEvaluationValue value)

Average squared difference between the logarithm of the predicted values and the logarithm of the actual (ground truth) value.

API name: msle

msle

public final DataframeRegressionSummary.Builder msle(Function<DataframeEvaluationValue.Builder,ObjectBuilder<DataframeEvaluationValue>> fn)

Average squared difference between the logarithm of the predicted values and the logarithm of the actual (ground truth) value.

API name: msle

rSquared

public final DataframeRegressionSummary.Builder rSquared(@Nullable
 DataframeEvaluationValue value)

Proportion of the variance in the dependent variable that is predictable from the independent variables.

API name: r_squared

rSquared

public final DataframeRegressionSummary.Builder rSquared(Function<DataframeEvaluationValue.Builder,ObjectBuilder<DataframeEvaluationValue>> fn)

Proportion of the variance in the dependent variable that is predictable from the independent variables.

API name: r_squared

self

protected DataframeRegressionSummary.Builder self()

Specified by:

self in class WithJsonObjectBuilderBase<DataframeRegressionSummary.Builder>

build

public DataframeRegressionSummary build()

Builds a DataframeRegressionSummary.

Specified by:

build in interface ObjectBuilder<DataframeRegressionSummary>

Throws:

NullPointerException - if some of the required fields are null.