Abstract
This paper presents a new method of clustering and classification. Here is discussed a new method of clustering based on defining the heat function. Shahyat algorithm can be implemented either in a supervised or unsupervised manner. We consider each pattern as a heat source; the points of feature space are affected by the heat of all patterns. Therefore, the closer the patterns, the higher the heat, and we can determine compact regions of feature space noticing the heat of space. We calculate the heat of patterns, and choose cluster centers based on their heat. Finally, we solve the iris clustering problem and present several specifications of shahyat algorithm.
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© 2009 Springer Science+Business Media, LLC
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Khayat, O., Shahdoosti, H.R. (2009). Shahyat Algorithm as a Clustering Method. In: Mastorakis, N., Mladenov, V., Kontargyri, V. (eds) Proceedings of the European Computing Conference. Lecture Notes in Electrical Engineering, vol 28. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-85437-3_14
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DOI: https://doi.org/10.1007/978-0-387-85437-3_14
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Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-84818-1
Online ISBN: 978-0-387-85437-3
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