Abstract
A new algorithm is proposed for clustering, drawing on the ideas underlying messy genetic algorithms. Individuals in each generation are clusters whose fitness depends on the mean distance between samples in the same cluster. The algorithm consists of four phases: initialization, cluster-formation, operator-application, and final cluster-selection. Four operators are used: merge, split, erode, and gobble. The algorithm is fairly general, and the function to be optimized can be modified to obtain good clusters that satisfy different requirements.
| Original language | English (US) |
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| Pages | 831-836 |
| Number of pages | 6 |
| State | Published - 1993 |
| Event | Proceedings of the 1993 Artificial Neural Networks in Engineering, ANNIE'93 - St.Louis, MO, USA Duration: Nov 14 1993 → Nov 17 1993 |
Other
| Other | Proceedings of the 1993 Artificial Neural Networks in Engineering, ANNIE'93 |
|---|---|
| City | St.Louis, MO, USA |
| Period | 11/14/93 → 11/17/93 |
ASJC Scopus subject areas
- Software