com.amazonaws.services.forecast.model

Class EvaluationParameters

java.lang.Object

com.amazonaws.services.forecast.model.EvaluationParameters

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable

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

Parameters that define how to split a dataset into training data and testing data, and the number of iterations to perform. These parameters are specified in the predefined algorithms and can be overridden in the CreatePredictor request.

For example, suppose that you have a dataset with data collection frequency set to every day and you have 200 days worth of data (that is, 200 data points). Now suppose that you set the NumberOfBacktestWindows to 2 and the BackTestWindowOffset parameter to 20. The algorithm splits the data twice. The first time, the algorithm trains the model using the first 180 data points and uses the last 20 data points for evaluation. The second time, the algorithm trains the model using the first 160 data points and uses the last 40 data points for evaluation.

See Also:

AWS API Documentation, Serialized Form

Constructor Summary

Constructors

Constructor and Description
EvaluationParameters()

Method Summary

Modifier and Type	Method and Description
EvaluationParameters	clone()
boolean	equals(Object obj)
Integer	getBackTestWindowOffset() The point from the end of the dataset where you want to split the data for model training and evaluation.
Integer	getNumberOfBacktestWindows() The number of times to split the input data.
int	hashCode()
void	marshall(ProtocolMarshaller protocolMarshaller)
void	setBackTestWindowOffset(Integer backTestWindowOffset) The point from the end of the dataset where you want to split the data for model training and evaluation.
void	setNumberOfBacktestWindows(Integer numberOfBacktestWindows) The number of times to split the input data.
String	toString() Returns a string representation of this object.
EvaluationParameters	withBackTestWindowOffset(Integer backTestWindowOffset) The point from the end of the dataset where you want to split the data for model training and evaluation.
EvaluationParameters	withNumberOfBacktestWindows(Integer numberOfBacktestWindows) The number of times to split the input data.

Methods inherited from class java.lang.Object

finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

EvaluationParameters

public EvaluationParameters()

Method Detail

setNumberOfBacktestWindows

public void setNumberOfBacktestWindows(Integer numberOfBacktestWindows)

The number of times to split the input data. The default is 1. The range is 1 through 5.

Parameters:

numberOfBacktestWindows - The number of times to split the input data. The default is 1. The range is 1 through 5.

getNumberOfBacktestWindows

public Integer getNumberOfBacktestWindows()

The number of times to split the input data. The default is 1. The range is 1 through 5.

Returns:

The number of times to split the input data. The default is 1. The range is 1 through 5.

withNumberOfBacktestWindows

public EvaluationParameters withNumberOfBacktestWindows(Integer numberOfBacktestWindows)

The number of times to split the input data. The default is 1. The range is 1 through 5.

Parameters:

numberOfBacktestWindows - The number of times to split the input data. The default is 1. The range is 1 through 5.

Returns:

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

setBackTestWindowOffset

public void setBackTestWindowOffset(Integer backTestWindowOffset)

The point from the end of the dataset where you want to split the data for model training and evaluation. The value is specified as the number of data points.

Parameters:

backTestWindowOffset - The point from the end of the dataset where you want to split the data for model training and evaluation. The value is specified as the number of data points.

getBackTestWindowOffset

public Integer getBackTestWindowOffset()

The point from the end of the dataset where you want to split the data for model training and evaluation. The value is specified as the number of data points.

Returns:

The point from the end of the dataset where you want to split the data for model training and evaluation. The value is specified as the number of data points.

withBackTestWindowOffset

public EvaluationParameters withBackTestWindowOffset(Integer backTestWindowOffset)

The point from the end of the dataset where you want to split the data for model training and evaluation. The value is specified as the number of data points.

Parameters:

backTestWindowOffset - The point from the end of the dataset where you want to split the data for model training and evaluation. The value is specified as the number of data points.

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 EvaluationParameters clone()

Overrides:

clone in class Object

marshall

public void marshall(ProtocolMarshaller protocolMarshaller)

Specified by:

marshall in interface StructuredPojo