Automatic Clustering with Single Optimal Solution

Details Automatic Clustering with Single Optimal Solution Automatic Clustering with Single Optimal Solution

2012-02-08

arxiv.org/abs/1202.1587v1

Computer Engineering and Intelligent Systems, 2011, vol no.2 no.4 pp149-161

Computer Science

Computer Vision and Pattern Recognition

13 pages,4 Tables, 3 figures

Scientific paper

Determining optimal number of clusters in a dataset is a challenging task. Though some methods are available, there is no algorithm that produces unique clustering solution. The paper proposes an Automatic Merging for Single Optimal Solution (AMSOS) which aims to generate unique and nearly optimal clusters for the given datasets automatically. The AMSOS is iteratively merges the closest clusters automatically by validating with cluster validity measure to find single and nearly optimal clusters for the given data set. Experiments on both synthetic and real data have proved that the proposed algorithm finds single and nearly optimal clustering structure in terms of number of clusters, compactness and separation.

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