Warnekar, CS and Krishna, G (1979) A heuristic clustering algorithm using union of overlapping pattern-cells. In: Pattern Recognition, 11 (2). pp. 85-93.
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Relative geometric arrangements of the sample points, with reference to the structure of the imbedding space, produce clusters. Hence, if each sample point is imagined to acquire a volume of a small M-cube (called pattern-cell), depending on the ranges of its (M) features and number (N) of samples; then overlapping pattern-cells would indicate naturally closer sample-points. A chain or blob of such overlapping cells would mean a cluster and separate clusters would not share a common pattern-cell between them. The conditions and an analytic method to find such an overlap are developed. A simple, intuitive, nonparametric clustering procedure, based on such overlapping pattern-cells is presented. It may be classified as an agglomerative, hierarchical, linkage-type clustering procedure. The algorithm is fast, requires low storage and can identify irregular clusters. Two extensions of the algorithm, to separate overlapping clusters and to estimate the nature of pattern distributions in the sample space, are also indicated.
| Item Type: | Journal Article |
|---|---|
| Publication: | Pattern Recognition |
| Publisher: | Elsevier Science |
| Additional Information: | Copyright of this article belongs to Elsevier Science. |
| Keywords: | Sample points; Geometric arrangements; Pattern-cells; Overlap; Union; Analytic method; Transformation; Clusters |
| Department/Centre: | Division of Electrical Sciences > Electrical Engineering |
| Date Deposited: | 22 Dec 2010 11:36 |
| Last Modified: | 22 Dec 2010 11:36 |
| URI: | http://eprints.iisc.ac.in/id/eprint/34402 |
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