Abstract
In this paper, we present a novel algorithm for performing k-means clustering using cuckoo search. A pending problem of K-Means clustering algorithm is that the performance is affected by the original cluster centers. In this paper the K-Means algorithm is improved by cuckoo search and the initial cluster centers are generated by cuckoo search. The experiments and comparisons with the classical K-Means algorithm indicate that the improved k-mean clustering algorithm has obvious advantages on execution time.
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Acknowledgments
This work was supported by Beijing Higher Education Young Elite Teacher Project (YETP1532); Beijing Excellent Talents funded projects (2013D005009000003). The outstanding talents project supported by Beijing municipal Party Committee Organization Department (No.2013D005009000003).
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Zhao, M., Tang, H., Guo, J., Sun, Y. (2016). A Data Clustering Algorithm Using Cuckoo Search. In: Hung, J., Yen, N., Li, KC. (eds) Frontier Computing. Lecture Notes in Electrical Engineering, vol 375. Springer, Singapore. https://doi.org/10.1007/978-981-10-0539-8_23
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DOI: https://doi.org/10.1007/978-981-10-0539-8_23
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Online ISBN: 978-981-10-0539-8
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