The MCL algorithm is short for the Markov Cluster Algorithm, a fast and scalable unsupervised cluster algorithm for graphs based on simulation of (stochastic) flow in graphs. The algorithm was invented/discovered by Stijn van Dongen at the Centre for Mathematics and Computer Science (also known as CWI) in the Netherlands. The input / output parsers, the webservices and the web interfaces were developped by Sylvain Brohée.
Input and output formats
The accepted input formats are GML, tab-delimited and adjacency matrix.
For more explanations about these, refer to the manual of convert-graph.
A tab-delimited text file with 2 columns. The first column
indicates the element, the second column the class (cluster).
Column specifications (only for tab-delimited format)
Source and target column. Columns containing the source and target nodes.
Weight or label column Column containing the weight or the label on the edge.
This value is the main handle for affecting cluster granularity. It is usually chosen somewhere in the range [1.2-5.0]. Inflation of 5.0 will tend to result in fine-grained clusterings, and inflation of 1.2 will tend to result in very coarse grained clusterings. Your mileage will vary depending on the characteristics of your data.