计算机应用 ›› 2019, Vol. 39 ›› Issue (7): 1883-1887.DOI: 10.11772/j.issn.1001-9081.2018122483

• 人工智能 • 上一篇    下一篇

基于K最近邻样本平均距离的代价敏感算法的集成

杨浩1, 王宇1, 张中原2   

  1. 1. 河海大学 计算机与信息学院, 南京 211100;
    2. 滑铁卢大学 计算机系, 安大略 滑铁卢 N2L 3G1, 加拿大
  • 收稿日期:2018-12-17 修回日期:2019-01-28 出版日期:2019-07-10 发布日期:2019-03-28
  • 通讯作者: 杨浩
  • 作者简介:杨浩(1995-),男,江苏淮安人,硕士研究生,主要研究方向:代价敏感学习、异常检测;王宇(1979-),男,云南昆明人,副研究员,博士,主要研究方向:云计算、数据管理;张中原(1997-),男,江苏南京人,主要研究方向:人工智能、生物信息学。
  • 基金资助:

    国家自然青年科学基金资助项目(61103017);中国科学院感知中国先导专项子课题项目(XDA06040504)。

Integration of cost-sensitive algorithms based on average distance of K-nearest neighbor samples

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