The Generalization Ability of Online SVM Classification Based on Markov Sampling

著录项

• 来源
  《Neural Networks and Learning Systems, IEEE Transactions on》 |2015年第3期|628-639|共12页
• 作者

  Xu J.; Yan Tang Y.; Zou B.; Xu Z.; Li L.; Lu Y.;

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• 作者单位

  Faculty of Computer Science and Information Engineering, Hubei University, Wuhan, China;

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• 收录信息
• 原文格式 PDF
• 正文语种 eng
• 中图分类
• 关键词

  Algorithm design and analysis; Classification algorithms; Educational institutions; Machine learning algorithms; Markov processes; Support vector machines; Training; Generalization ability; Markov sampling; online support vector machine (SVM) classification; uniformly ergodic Markov chain (u.e.M.c.); uniformly ergodic Markov chain (u.e.M.c.).;

  机译：算法设计与分析;分类算法;教育机构;机器学习算法;马尔可夫过程;支持向量机;训练;泛化能力;马尔可夫采样;在线支持向量机（SVM）分类;均匀遍历的马尔可夫链（ueMc）;均匀遍历的马尔可夫链（ueMc）。;