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Incremental construction of rule ensembles using classifiers produced by different class orderings
(IEEE, 2016)
In this paper, we discuss a novel approach to incrementally construct a rule ensemble. The approach constructs an ensemble from a dynamically generated set of rule classifiers. Each classifier in this set is trained by ...
Feature extraction from discrete attributes
(IEEE, 2010)
In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we extract new features by combining k discrete attributes, where for each ...