gov.sandia.cognition.learning.function.cost

Class AbstractParallelizableCostFunction

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction<Vector,Vector>

gov.sandia.cognition.learning.function.cost.AbstractParallelizableCostFunction

All Implemented Interfaces:

Evaluator<Evaluator<? super Vector,? extends Vector>,java.lang.Double>, CostFunction<Evaluator<? super Vector,? extends Vector>,java.util.Collection<? extends InputOutputPair<? extends Vector,Vector>>>, DifferentiableCostFunction, ParallelizableCostFunction, SupervisedCostFunction<Vector,Vector>, PerformanceEvaluator<Evaluator<? super Vector,? extends Vector>,java.util.Collection<? extends InputOutputPair<? extends Vector,Vector>>,java.lang.Double>, SupervisedPerformanceEvaluator<Vector,Vector,Vector,java.lang.Double>, CloneableSerializable, Summarizer<TargetEstimatePair<? extends Vector,? extends Vector>,java.lang.Double>, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

SumSquaredErrorCostFunction

public abstract class AbstractParallelizableCostFunction
extends AbstractSupervisedCostFunction<Vector,Vector>
implements ParallelizableCostFunction

Partial implementation of the ParallelizableCostFunction

Since:

2.1

Author:

Kevin R. Dixon

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AbstractParallelizableCostFunction(java.util.Collection<? extends InputOutputPair<? extends Vector,Vector>> costParameters) Creates a new instance of AbstractParallelizableCostFunction

Method Summary

Modifier and Type	Method and Description
Vector	computeParameterGradient(GradientDescendable function) Differentiates function with respect to its parameters.
java.lang.Double	evaluate(Evaluator<? super Vector,? extends Vector> evaluator) Computes the cost of the given target.

Methods inherited from class gov.sandia.cognition.learning.function.cost.AbstractSupervisedCostFunction

clone, evaluatePerformance, getCostParameters, setCostParameters, summarize

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

evaluatePerformance

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.learning.function.cost.ParallelizableCostFunction

computeParameterGradientAmalgamate, computeParameterGradientPartial, evaluateAmalgamate, evaluatePartial

Methods inherited from interface gov.sandia.cognition.learning.function.cost.CostFunction

clone, getCostParameters, setCostParameters

Methods inherited from interface gov.sandia.cognition.util.Summarizer

summarize

Methods inherited from interface gov.sandia.cognition.learning.performance.SupervisedPerformanceEvaluator

evaluatePerformance

Methods inherited from interface gov.sandia.cognition.learning.performance.PerformanceEvaluator

evaluatePerformance

Constructor Detail

AbstractParallelizableCostFunction

public AbstractParallelizableCostFunction(java.util.Collection<? extends InputOutputPair<? extends Vector,Vector>> costParameters)

Creates a new instance of AbstractParallelizableCostFunction

Parameters:

costParameters - Dataset to use

Method Detail

evaluate

public java.lang.Double evaluate(Evaluator<? super Vector,? extends Vector> evaluator)

Description copied from interface: CostFunction

Computes the cost of the given target.

Specified by:

evaluate in interface Evaluator<Evaluator<? super Vector,? extends Vector>,java.lang.Double>

Specified by:

evaluate in interface CostFunction<Evaluator<? super Vector,? extends Vector>,java.util.Collection<? extends InputOutputPair<? extends Vector,Vector>>>

Overrides:

evaluate in class AbstractSupervisedCostFunction<Vector,Vector>

Parameters:

evaluator - The object to evaluate.

Returns:

The cost of the given object.

computeParameterGradient

public Vector computeParameterGradient(GradientDescendable function)

Description copied from interface: DifferentiableCostFunction

Differentiates function with respect to its parameters.

Specified by:

computeParameterGradient in interface DifferentiableCostFunction

Parameters:

function - The object to differentiate.

Returns:

Derivatives of the object with respect to the cost function.