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.
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Maschine Learning Methods for Fuzzy Pattern Tree Induction Robin Senge, PhD-Thesis, University of Marburg, 2014 http://archiv.ub.uni-marburg.de/diss/z2014/0391/pdf/drs.pdf
Top-down induction of fuzzy pattern trees Robin Senge, Eyke Hüllermeier - IEEE Transactions on Fuzzy Systems, 2011 https://www.researchgate.net/profile/Robin_Senge/publication/224196209_Top-Down_Induction_of_Fuzzy_Pattern_Trees/links/5839dcde08ae3d91723f6418/Top-Down-Induction-of-Fuzzy-Pattern-Trees.pdf
Evolving fuzzy pattern trees for binary classification on data streams Ammar Shaker, Robin Senge, Eyke Hüllermeier - Information Sciences, 2013 https://cs.uni-paderborn.de/fileadmin/informatik/fg/is/Publications/EFPT.pdf
Pattern trees for regression and fuzzy systems modeling Robin Senge, Eyke Hüllermeier - 2010 IEEE International Cnoference on Fuzzy Systems, 2010 https://www.researchgate.net/profile/Robin_Senge/publication/224177003_Pattern_trees_for_regression_and_fuzzy_systems_modeling/links/5469d5390cf2f5eb180520e0/Pattern-trees-for-regression-and-fuzzy-systems-modeling.pdf