Considering diversity and accuracy simultaneously for ensemble pruning
This paper proposes a new Modified Backtracking Ensemble Pruning algorithm (ModEnPBT), which is based upon the design idea of our previously proposed Ensemble Pruning via Backtracking algorithm (EnPBT), and however, aiming at overcoming its drawback of redundant solution space definition. Solution space of ModEnPBT is compact with no repeated solution vectors, therefore it possesses relatively higher searching efficiency compared with EnPBT algorithm. ModEnPBT still belongs to the category of Backtracking algorithm, which can systematically search for the solutions of a problem in a manner nsemble pruning elective ensemble acktracking algorithm nsemble Pruning via Backtracking lgorithm (EnPBT) odified Ensemble Pruning via acktracking algorithm (ModEnPBT) of depth-first, which is suitable for solving all those large-scale combinatorial optimization problems. Experimental results on three benchmark classification tasks demonstrate the validity and effectiveness of the proposed ModEnPBT. © 2013 Elsevier B.V. All rights reserved.