Uncertainty in clustering and classification

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Abstract

Clustering and classification are among the most important problem tasks in the realm of data analysis, data mining and machine learning. In fact, while clustering can be seen as the most popular representative of unsupervised learning, classification (together with regression) is arguably the most frequently considered task in supervised learning. Even though the literature on clustering and classification abounds, the interest in these topics seems to be unwaning, both from a research and application point of view. © 2010 Springer-Verlag Berlin Heidelberg.

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Hüllermeier, E. (2010). Uncertainty in clustering and classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6379 LNAI, pp. 16–19). https://doi.org/10.1007/978-3-642-15951-0_6

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