Probabilistic Combination of Text Classiï¬ers Using Reliability Indicators: Models and Results - Bennett, Paul N.; Dumais, Susan; Horvitz, Eric (Proceedings of SIGIR 02, 2002)
The intuition that different text classiﬁers behave in qualitatively different ways has long motivated attempts to build a better metaclassiﬁer via some combination of classiﬁers. We introduce a probabilistic method for combining classiﬁers that considers the context sensitive reliabilities of contributing classiﬁers. The method harnesses reliability indicators—variables that provide a valuable signal about the performance of classiﬁers in different situations. We provide background, present procedures for building metaclassiﬁers that take into consideration both reliability indicators and classiﬁer outputs, and review a set of comparative studies undertaken to evaluate the methodology.