Abstract
This paper presents Dp1, an incremental clustering algorithm that accepts a description of the expected performance task — the goal of learning — and uses that description to alter its learning bias. With different goals Dp1 addresses a wide range of empirical learning tasks from supervised to unsupervised learning. At one extreme, Dp1 performs the same task as does ID3, and at the other, it performs the same task as does Cobweb.
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© 1994 Springer-Verlag Berlin Heidelberg
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Martin, J.D. (1994). DP1: Supervised and unsupervised clustering. In: Bergadano, F., De Raedt, L. (eds) Machine Learning: ECML-94. ECML 1994. Lecture Notes in Computer Science, vol 784. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57868-4_82
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DOI: https://doi.org/10.1007/3-540-57868-4_82
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