See: Description
| Interface | Description |
|---|---|
| ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> |
The ClusterDivergenceFunction interface defines a function that computes
the divergence between a cluster and some other object.
|
| ClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> |
The ClusterToClusterDivergenceFunction defines a DivergenceFunction between
two clusters of the same data type.
|
| WithinClusterDivergence<ClusterType extends Cluster<DataType>,DataType> |
Defines a function that computes the divergence of the elements in a cluster.
|
| Class | Description |
|---|---|
| AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> |
The AbstractClusterToClusterDivergenceFunction class is an abstract class
that helps out implementations of ClusterToClusterDivergenceFunction
implementations by holding a DivergenceFunction between elements of a
cluster.
|
| CentroidClusterDivergenceFunction<DataType> |
The CentroidClusterDivergenceFunction class implements a divergence function
between a cluster and an object by computing the divergence between the
center of the cluster and the object.
|
| ClusterCentroidDivergenceFunction<DataType> |
The ClusterCentroidDivergenceFunction class implements the distance
between two clusters by computing the distance between the cluster's
centroid.
|
| ClusterCompleteLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> |
The ClusterCompleteLinkDivergenceFunction class implements the complete
linkage distance metric between two clusters.
|
| ClusterMeanLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> |
The ClusterMeanLinkDivergenceFunction class implements the mean linkage
distance metric between two clusters.
|
| ClusterSingleLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> |
The ClusterSingleLinkDivergenceFunction class implements the complete
linkage distance metric between two clusters.
|
| GaussianClusterDivergenceFunction |
The GaussianClusterDivergenceFunction class implements a divergence
function between a Gaussian cluster and a vector, which is calculated
by finding the likelihood that the vector was generated from that Gaussian
and then returning the negative of the likelihood since it is a divergence
measure, not a similarity measure.
|
| WithinClusterDivergenceWrapper<ClusterType extends Cluster<DataType>,DataType> |
Accumulates the results of a
ClusterDivergenceFunction by summing the
divergence of each point to its cluster. |
| WithinNormalizedCentroidClusterCosineDivergence<V extends Vectorizable> |
This class calculates the total cosine divergence between all members of a
cluster and the cluster's centroid
|