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An asymptotically optimal kernel combined classifier

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  • Mojirsheibani, Majid
  • Kong, Jiajie

Abstract

A kernel ensemble classifier is developed for accurate classification based on several initial classifiers. A data-driven choice of the smoothing parameter of the kernel is considered and the resulting classifier is shown to be asymptotically optimal. Therefore, the proposed combined classifier asymptotically outperforms each individual classifier.

Suggested Citation

  • Mojirsheibani, Majid & Kong, Jiajie, 2016. "An asymptotically optimal kernel combined classifier," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 91-100.
    • Handle: RePEc:eee:stapro:v:119:y:2016:i:c:p:91-100
    DOI: 10.1016/j.spl.2016.07.017
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    References listed on IDEAS

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    7. Adler, Werner & Brenning, Alexander & Potapov, Sergej & Schmid, Matthias & Lausen, Berthold, 2011. "Ensemble classification of paired data," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1933-1941, May.
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