Multiobjective sparse ensemble learning by means of evolutionary algorithms
Abstract
Ensemble learning can improve the performance of individual classifiers by combining their decisions. The sparseness of ensemble learning has attracted much attention in recent years. In this paper, a novel multiobjective sparse ensemble learning (MOSEL) model is proposed. Firstly, to describe the ensemble classifiers more precisely the detection error trade-off (DET) curve is taken into consideration. The sparsity ratio (sr) is treated as the...
Paper Details
Title
Multiobjective sparse ensemble learning by means of evolutionary algorithms
Published Date
Jul 1, 2018
Journal
Volume
111
Pages
86 - 100
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