Machine Learning in Java - Second Edition

Clustering using ELKI

ELKI supports many clustering algorithms. A few are listed as follows:

• Affinity propagation clustering algorithm: This is a cluster analysis that uses affinity propagation.
• DBSCAN: This is density based clustering especially for the applications with noise; it finds the sets in the database on the basis of density.
• EM: This algorithm creates clusters based on the expectation maximization algorithm.
• AGNES: Hierarchical agglomerative clustering (HAC), or agglomerative nesting (AGNES), is a classic hierarchical clustering algorithm. 
• SLINK: This is the single link algorithm.
• CLINK: This is used for complete linkage.
• HDBSCAN: This is an extracting cluster hierarchy.

Also, KMeansSort, KMeansCompare, KMedianLloyd, KMediodsEM, ...