Abstract
Over the last years, researchers have focused their attention on a new approach, supervised clustering, that combines the main characteristics of both traditional clustering and supervised classification tasks. Motivated by the importance of pre-processing approaches in the traditional clustering context, this paper explores to what extent supervised pre-processing steps could help traditional clustering to obtain better performance on supervised clustering tasks. This paper reports experiments which show that indeed standard clustering algorithms are competitive compared to existing supervised clustering algorithms when supervised pre-processing steps are carried out.
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Ismaili, O.A., Lemaire, V., Cornuéjols, A. (2016). Supervised Pre-processings Are Useful for Supervised Clustering. In: Wilhelm, A., Kestler, H. (eds) Analysis of Large and Complex Data. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-319-25226-1_13
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DOI: https://doi.org/10.1007/978-3-319-25226-1_13
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