An Intelligent Search for Clustering

Abstract

The problem of clustering n-objects into m-classes may be viewed as a combinatorial optimization problem. The optimum classification of n-objects into m-classes is considered under the assumption that there exists a criterion by which each classification can be evaluated and ultimately the optimum classification can be obtained. Most clustering algorithms described in the literatures are iterative hill-climbing techniques which generally yield local optimum classification. In this text, we develop a clustering algorithm based on A* search with certain pruning feature. This algorithm determines the globally optimum classification and is computationally very efficient.

Indexing terms:

• Clustering
• Optimum pattern classification
• Combinational optimization
• A*—Search