com.amazonaws.services.forecast.model

Class WeightedQuantileLoss

java.lang.Object

com.amazonaws.services.forecast.model.WeightedQuantileLoss

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class WeightedQuantileLoss
extends Object
implements Serializable, Cloneable, StructuredPojo

The weighted loss value for a quantile. This object is part of the Metrics object.

See Also:

AWS API Documentation, Serialized Form

Constructor Summary

Constructors

Constructor and Description
WeightedQuantileLoss()

Method Summary

Modifier and Type	Method and Description
WeightedQuantileLoss	clone()
boolean	equals(Object obj)
Double	getLossValue() The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.
Double	getQuantile() The quantile.
int	hashCode()
void	marshall(ProtocolMarshaller protocolMarshaller) Marshalls this structured data using the given ProtocolMarshaller.
void	setLossValue(Double lossValue) The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.
void	setQuantile(Double quantile) The quantile.
String	toString() Returns a string representation of this object.
WeightedQuantileLoss	withLossValue(Double lossValue) The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.
WeightedQuantileLoss	withQuantile(Double quantile) The quantile.

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

WeightedQuantileLoss

public WeightedQuantileLoss()

Method Detail

setQuantile

public void setQuantile(Double quantile)

The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

Parameters:

quantile - The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

getQuantile

public Double getQuantile()

The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

Returns:

The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

withQuantile

public WeightedQuantileLoss withQuantile(Double quantile)

The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

Parameters:

quantile - The quantile. Quantiles divide a probability distribution into regions of equal probability. For example, if the distribution was divided into 5 regions of equal probability, the quantiles would be 0.2, 0.4, 0.6, and 0.8.

Returns:

Returns a reference to this object so that method calls can be chained together.

setLossValue

public void setLossValue(Double lossValue)

The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

Parameters:

lossValue - The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

getLossValue

public Double getLossValue()

The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

Returns:

The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

withLossValue

public WeightedQuantileLoss withLossValue(Double lossValue)

The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

Parameters:

lossValue - The difference between the predicted value and the actual value over the quantile, weighted (normalized) by dividing by the sum over all quantiles.

Returns:

Returns a reference to this object so that method calls can be chained together.

toString

public String toString()

Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.

Overrides:

toString in class Object

Returns:

A string representation of this object.

See Also:

Object.toString()

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

clone

public WeightedQuantileLoss clone()

Overrides:

clone in class Object

marshall

public void marshall(ProtocolMarshaller protocolMarshaller)

Description copied from interface: StructuredPojo

Marshalls this structured data using the given ProtocolMarshaller.

Specified by:

marshall in interface StructuredPojo

Parameters:

protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.