Top-down induction of clustering trees
arXiv (Cornell University)Published 21 November 2000Open access
Hendrik Blockeel, Luc De Raedt, Jan Ramon
Citations398
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Abstract
An approach to clustering is presented that adapts the basic top-down induction of decision trees method towards clustering. To this aim, it employs the principles of instance based learning. The resulting methodology is implemented in the TIC (Top down Induction of Clustering trees) system for first order clustering. The TIC system employs the first order logical decision tree representation of the inductive logic programming system Tilde. Various experiments with TIC are presented, in both propositional and relational domains.
Keywords
Computer Science
BiometricsClassification and Regression Trees.
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