gov.sandia.cognition.learning.performance

Class MeanSquaredErrorEvaluator<InputType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.learning.performance.AbstractSupervisedPerformanceEvaluator<InputType,java.lang.Double,java.lang.Double,java.lang.Double>

gov.sandia.cognition.learning.performance.MeanSquaredErrorEvaluator<InputType>

Type Parameters:

InputType - The type of the input to the evaluator to compute the performance of.

All Implemented Interfaces:

PerformanceEvaluator<Evaluator<? super InputType,? extends java.lang.Double>,java.util.Collection<? extends InputOutputPair<? extends InputType,java.lang.Double>>,java.lang.Double>, SupervisedPerformanceEvaluator<InputType,java.lang.Double,java.lang.Double,java.lang.Double>, CloneableSerializable, Summarizer<TargetEstimatePair<? extends java.lang.Double,? extends java.lang.Double>,java.lang.Double>, java.io.Serializable, java.lang.Cloneable

public class MeanSquaredErrorEvaluator<InputType>
extends AbstractSupervisedPerformanceEvaluator<InputType,java.lang.Double,java.lang.Double,java.lang.Double>

The MeanSquaredError class implements the method for computing the performance of a supervised learner for a scalar function by the mean squared between the target and estimated outputs.

Since:

2.0

Author:

Justin Basilico

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
MeanSquaredErrorEvaluator() Creates a new instance of MeanSquaredError.

Method Summary

Modifier and Type	Method and Description
static double	compute(java.util.Collection<? extends TargetEstimatePair<? extends java.lang.Double,? extends java.lang.Double>> data) Computes the mean squared error for the given pairs of values.
java.lang.Double	evaluatePerformance(java.util.Collection<? extends TargetEstimatePair<? extends java.lang.Double,? extends java.lang.Double>> data) Evaluates the performance accuracy of the given estimates against the given targets.

Methods inherited from class gov.sandia.cognition.learning.performance.AbstractSupervisedPerformanceEvaluator

evaluatePerformance, summarize

Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable

clone

Methods inherited from class java.lang.Object

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

Constructor Detail

MeanSquaredErrorEvaluator

public MeanSquaredErrorEvaluator()

Creates a new instance of MeanSquaredError.

Method Detail

evaluatePerformance

public java.lang.Double evaluatePerformance(java.util.Collection<? extends TargetEstimatePair<? extends java.lang.Double,? extends java.lang.Double>> data)

Evaluates the performance accuracy of the given estimates against the given targets.

Specified by:

evaluatePerformance in interface SupervisedPerformanceEvaluator<InputType,java.lang.Double,java.lang.Double,java.lang.Double>

Specified by:

evaluatePerformance in class AbstractSupervisedPerformanceEvaluator<InputType,java.lang.Double,java.lang.Double,java.lang.Double>

Parameters:

data - The target-estimate pairs to use to evaluate performance.

Returns:

The performance evaluation result.

compute

public static double compute(java.util.Collection<? extends TargetEstimatePair<? extends java.lang.Double,? extends java.lang.Double>> data)

Computes the mean squared error for the given pairs of values. The squared difference between the two values in each pair is computed and then the mean over all the values is returned.

Parameters:

data - The data to compute the mean squared error over.

Returns:

The mean squared error.