Abstract
Clustering with instance-level constraints has received much attention in the clustering community recently. Particularly, must-Link and cannot-Link constraints between a given pair of instances in the data set are common prior knowledge incorporated in many clustering algorithms today. This approach has been shown to be successful in guiding a number of famous clustering algorithms towards more accurate results. However, recent work has also shown that incorporation of must-link and cannot-link constraints makes clustering algorithms too much sensitive to ”assignment order of instances” and therefore results in consequent constraint-violation. In this paper, we propose a modified version of Cop-Kmeans which relies on a sequenced assignment of cannot-linked instances. In comparison with original Cop-Kmeans, experiments on four UCI data sets indicate that our method could effectively overcome the problem of ”constraint-violation”, yet with almost the same performance as that of Cop-Kmeans algorithm.
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Rutayisire, T., Yang, Y., Lin, C., Zhang, J. (2011). A Modified Cop-Kmeans Algorithm Based on Sequenced Cannot-Link Set. In: Yao, J., Ramanna, S., Wang, G., Suraj, Z. (eds) Rough Sets and Knowledge Technology. RSKT 2011. Lecture Notes in Computer Science(), vol 6954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24425-4_30
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DOI: https://doi.org/10.1007/978-3-642-24425-4_30
Publisher Name: Springer, Berlin, Heidelberg
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