Clustering Methods

Clustering Methods (technically also called Programs throughout this guide) can be executed by the framework, and be applied to data to calculate clusterings. In order to include a new clustering method and use it within the framework,

• the executable of the method has to be made available to the framework (an exception are Clustering Methods provided through the R framework),
• the method itself has to be specified in a configuration file (called program configuration)
• all other components (e.g. input and output formats) specified in the program configuration need to be available

The configuration file for a clustering method (short program configuration) contains all information required, such that the framework can execute the method in an automatized and autonomous way. These information include for example, among others, the name of the method, its supported input formats, its output format, its parameters (including type and valid range of values). An exact description of how program configurations look like and which options and settings need to be specified can be found in.

Standalone

Standalone programs come as an executable that can be performed by the framework, after they have been specified in a program configuration. The executable needs to be compatible to the server architecture clusteval runs on and they need to be executable (+x modifier).

R Programs (Rserve)

ClustEval supports the execution of R implementations. Arbitrary methods implemented in R can be used as a program, as long as they can be made available within R on the server. This implies that the corresponding R Program is available for your R version and that it can be compiled and installed on your server architecture.

Available Clustering Methods

ClustEval ships with a set of clustering methods:

• Affinity Propagation
• DBSCAN
• clusterONE
• clusterdp
• Fanny
• Hierarchical Clustering
• K-means
• MCODE
• Markov Clustering
• k-Medoids (PAM)
• Self Organizing Maps
• Spectral Clustering
• Transitivity Clustering

For every of these clustering methods a program configuration is also provided, such that they are directly usable from the start. Of course these program configurations can be modified and adapted to the user’s needs.

Extending ClustEval

How you can extend ClustEval with your own clustering methods is described under Clustering Methods.