Diversity Regularized Machine

  title={Diversity Regularized Machine},
  author={Yang Yu and Yu-Feng Li and Zhi-Hua Zhou},
Ensemble methods, which train multiple learners for a task, are among the state-of-the-art learning approaches. The diversity of the component learners has been recognized as a key to a good ensemble, and existing ensemble methods try different ways to encourage diversity, mostly by heuristics. In this paper, we propose the diversity regularized machine (DRM) in a mathematical programming framework, which efficiently generates an ensemble of diverse support vector machines (SVMs). Theoretical… CONTINUE READING
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