Package medusa.georgios.enhanced_mcl

Interface Summary

Interface	Description
Clusterer	A common interface for all clustering techniques.
Dataset	Interface for a data set.
DistanceMeasure	A distance measure is an algorithm to calculate the distance, similarity or correlation between two instances.
Instance	The interface for instances in a data set.

Class Summary

Class	Description
AbstractSimilarity	Abstract super class for all similarity measures.
DefaultDataset	Provides a standard data set implementation.
DoubleFormat	DoubleFormat formats double numbers into a specified digit format.
ExpDouble	ExpDouble represents a double-precision number by a mantissa, a decimal exponent and the number of digits in the mantissa, in order to allow formatting of the represented double.
Fold
List2Graph
MarkovClustering	MarkovClustering implements the Markov clustering (MCL) algorithm for graphs, using a HashMap-based sparse representation of a Markov matrix, i.e., an adjacency matrix m that is normalised to one.
MCL
My_MarkovClustering	My_MarkovClustering implements the Markov clustering (MCL) algorithm for graphs, using a HashMap-based sparse representation of a Markov matrix, i.e., an adjacency matrix m that is normalised to one.
SparseMatrix	SparseMatrix is a sparse matrix with row-major format.
SparseVector	SparseVector represents a sparse vector.
Vectors	Static vector manipulation routines for Matlab porting and other numeric operations.