See: Description
Interface  Description 

DivergenceFunctionContainer<FirstType,SecondType> 
Interface for a class that holds a divergence function.

Class  Description 

ChebyshevDistanceMetric 
An implementation of the Chebyshev distance, which is the absolute value of
the largest difference between two vectors in a single dimension.

CosineDistanceMetric 
The
CosineDistanceMetric class implements a semimetric between
two vectors based on the cosine between the vectors. 
DefaultDivergenceFunctionContainer<FirstType,SecondType> 
The
DefaultDivergenceFunctionContainer class implements an object
that holds a divergence function. 
DivergencesEvaluator<InputType,ValueType> 
Evaluates the divergence (distance) between an input and a list of values,
storing the resulting divergence values in a vector.

DivergencesEvaluator.Learner<DataType,InputType,ValueType> 
A learner adapter for the
DivergencesEvaluator . 
EuclideanDistanceMetric 
The
EuclideanDistanceMetric implements a distance metric that
computes the Euclidean distance between two points. 
EuclideanDistanceSquaredMetric 
The
EuclideanDistanceSquaredMetric implements a distance metric
that computes the squared Euclidean distance between two points. 
IdentityDistanceMetric 
A distance metric that is 0 if two objects are equal and 1 if they are not.

ManhattanDistanceMetric 
The
ManhattanDistanceMetric class implements a distance metric
between two vectors that is implemented as the sum of the absolute value of
the difference between the elements in the vectors. 
MinkowskiDistanceMetric 
An implementation of the Minkowski distance metric.

WeightedEuclideanDistanceMetric 
A distance metric that weights each dimension of a vector differently before
computing Euclidean distance.
