Abstract
Genetic Algorithms (GAs) are generally portrayed as a search procedure which can optimize functions based on a limited sample of function values. In this paper, an objective function based on minimal spanning tree (MST) of data points is proposed for clustering and GAs have been used in an attempt to optimize the specified objective function in order to detect the natural grouping in a given data set. Several experiments on synthetic data set in \({\frak R}^2\) show the utility of the proposed method. The method is also applicable to any higher dimensional data.
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Chowdhury, N., Jana, P. (2004). Finding the Natural Groupings in a Data Set Using Genetic Algorithms. In: Manandhar, S., Austin, J., Desai, U., Oyanagi, Y., Talukder, A.K. (eds) Applied Computing. AACC 2004. Lecture Notes in Computer Science, vol 3285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30176-9_4
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DOI: https://doi.org/10.1007/978-3-540-30176-9_4
Publisher Name: Springer, Berlin, Heidelberg
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