Aggregating classifiers via Rademacher-Walsh polynomials

作者：Mojirsheibani Majid^*; Montazeri Zahra

来源：Journal of Statistical Computation and Simulation, 2015, 85(6): 1187-1199.

DOI：10.1080/00949655.2013.869695

• combined classification
• classifier aggregation
• consistency
• misclassification error rate

Methods are proposed to combine several individual classifiers in order to develop more accurate classification rules. The proposed algorithm uses Rademacher-Walsh polynomials to combine M (>= 2) individual classifiers in a nonlinear way. The resulting classifier is optimal in the sense that its misclassification error rate is always less than, or equal to, that of each constituent classifier. A number of numerical examples (based on both real and simulated data) are also given. These examples demonstrate some new, and far-reaching, benefits of working with combined classifiers.

• 出版日期2015-4-13