gov.sandia.cognition.learning.algorithm.clustering.divergence
Class AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType>
java.lang.Object
gov.sandia.cognition.util.AbstractCloneableSerializable
gov.sandia.cognition.learning.function.distance.DefaultDivergenceFunctionContainer<DataType,DataType>
gov.sandia.cognition.learning.algorithm.clustering.divergence.AbstractClusterToClusterDivergenceFunction<ClusterType,DataType>
- Type Parameters:
ClusterType
- type of Cluster<DataType>
used in the
learn()
methodDataType
- The algorithm operates on a Collection<DataType>
,
so DataType
will be something like Vector or String
- All Implemented Interfaces:
- ClusterToClusterDivergenceFunction<ClusterType,DataType>, DivergenceFunctionContainer<DataType,DataType>, DivergenceFunction<ClusterType,ClusterType>, CloneableSerializable, Serializable, Cloneable
- Direct Known Subclasses:
- ClusterCentroidDivergenceFunction, ClusterCompleteLinkDivergenceFunction, ClusterMeanLinkDivergenceFunction, ClusterSingleLinkDivergenceFunction
@CodeReview(reviewer="Kevin R. Dixon",
date="2008-07-23",
changesNeeded=false,
comments="Looks fine.")
public abstract class AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType>
- extends DefaultDivergenceFunctionContainer<DataType,DataType>
- implements ClusterToClusterDivergenceFunction<ClusterType,DataType>
The AbstractClusterToClusterDivergenceFunction class is an abstract class
that helps out implementations of ClusterToClusterDivergenceFunction
implementations by holding a DivergenceFunction between elements of a
cluster.
- Since:
- 1.0
- Author:
- Justin Basilico
- See Also:
- Serialized Form
AbstractClusterToClusterDivergenceFunction
public AbstractClusterToClusterDivergenceFunction(DivergenceFunction<? super DataType,? super DataType> divergenceFunction)
- Creates a new instance of AbstractClusterToClusterDivergenceFunction
- Parameters:
divergenceFunction
- The divergence function to use between
elements.