gov.sandia.cognition.learning.function.cost
Class KolmogorovSmirnovDivergence<DataType extends Number>

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.learning.function.cost.AbstractCostFunction<UnivariateDistribution<DataType>,Collection<? extends DataType>>
          extended by gov.sandia.cognition.learning.function.cost.KolmogorovSmirnovDivergence<DataType>
Type Parameters:
DataType - Type of data generated by the Distribution
All Implemented Interfaces:
Evaluator<UnivariateDistribution<DataType>,Double>, CostFunction<UnivariateDistribution<DataType>,Collection<? extends DataType>>, CloneableSerializable, Serializable, Cloneable

public class KolmogorovSmirnovDivergence<DataType extends Number>
extends AbstractCostFunction<UnivariateDistribution<DataType>,Collection<? extends DataType>>

CostFunction that induces a CDF that most-closely resembles the target distribution according to the Kolmogorov-Smirnov (K-S) test.

See Also:
Serialized Form

Field Summary
 
Fields inherited from class gov.sandia.cognition.learning.function.cost.AbstractCostFunction
costParameters
 
Constructor Summary
KolmogorovSmirnovDivergence()
          Default constructor
KolmogorovSmirnovDivergence(Collection<? extends DataType> costParameters)
          Creates a new instance of KolmogorovSmirnovDivergence
 
Method Summary
 Double evaluate(UnivariateDistribution<DataType> target)
          Computes the cost of the given target.
 
Methods inherited from class gov.sandia.cognition.learning.function.cost.AbstractCostFunction
clone, getCostParameters, setCostParameters
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

KolmogorovSmirnovDivergence

public KolmogorovSmirnovDivergence()
Default constructor


KolmogorovSmirnovDivergence

public KolmogorovSmirnovDivergence(Collection<? extends DataType> costParameters)
Creates a new instance of KolmogorovSmirnovDivergence

Parameters:
costParameters - Data generated by the target distribution
Method Detail

evaluate

public Double evaluate(UnivariateDistribution<DataType> target)
Description copied from interface: CostFunction
Computes the cost of the given target.

Parameters:
target - The object to evaluate.
Returns:
The cost of the given object.