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SCaVis manual

jMinHep manual

JMinHEP is a framework for clustering analysis, i.e. for non-supervised learning in which the classification process does not depend on a priory information . The program is a pure JAVA-based application and includes the following algorithms:

  • K-means clustering analysis (single and multi pass)
  • C-means (fuzzy) algorithm
  • Agglomerative hierarchical clustering
Snippet from Wikipedia: Cluster analysis

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters).

A good tutorial of clustering algorithms is here.

The algorithms can run for a fixed cluster mode and for a best estimate, i.e. when the number of clusters is not a priory given but is found after estimation of the cluster compactness. The data points can be defined in multidimensional space. At present, the distance measure is euclidean.

You can run K-means and hierarchical clustering algorithms in the following modes:

  • K-means algorithm fixed cluster mode with single seed event
  • K-means algorithm for multiple iterations
  • K-means clustering using exchange method for best estimate
  • K-means clustering using exchange method
  • Hierarchical clustering algorithm
  • Hierarchical clustering algorithm, best estimate

Download and install

Download jMinHep from the JMinHep web page. This version is completely self-contained and does not require additional libraries. The source code is included. The program is a part of the SCaVis computational environment. You can also run jMinHep inside ScaVis. There is a dedicated example using Java scripting in the ScaVis manual.

After downloading the package from the JMinHep web page, unzip the file and run it. Here is an example for Mac/Linux:

cd jminhep
java -jar jminhep.jar

For Windows, unzip the file and launch it by clicking on the jar file “jminhep.jar”.

You will see the GUI:


How to run and examples

Sorry, unregistered users have a limited access to the jMinHep manual. jMinHep is a part of SCaVis , although it can be used as a stand-alone self-contained program. One can unlock jMinHep manual after becoming a full SCaVis member of jWork.ORG. The protected sections explain how to run jMinHep, how to write Java code using this library and give Java API links.

S.Chekanov 2013/11/29 21:54

jminhep.txt · Last modified: 2013/12/03 20:40 by admin
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