Top-Down Induction of Fuzzy Pattern Trees

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Top-Down Induction of Fuzzy Pattern Trees
Fuzzy pattern tree induction was recently introduced as a novel machine learning method for classification. Roughly speaking, a pattern tree is a hierarchical, tree-like structure, whose inner nodes are marked with generalized (fuzzy) logical operators and whose leaf nodes are associated with fuzzy predicates on input attributes. A pattern tree classifier is composed of an ensemble of such pattern trees, one for each class label. This type of classifier is interesting for several reasons. For example, since a single pattern tree can be considered as a kind of logical description of a class, it is quite appealing from an interpretation point of view. Moreover, in terms of classification accuracy, the method has shown promising performance in first experimental studies. Yet, as will be argued in this paper, the algorithm that has originally been proposed for learning fuzzy pattern trees from data offers scope for improvement. Here, we propose a new method that modifies the origin...
R. Senge, Eyke Hüllermeier
Added 15 May 2011
Updated 15 May 2011
Type Journal
Year 2011
Where TFS
Authors R. Senge, Eyke Hüllermeier
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