计算机科学 ›› 2011, Vol. 38 ›› Issue (8): 242-244.

• 人工智能 • 上一篇    下一篇

基于超椭球的多类文本分类算法研究

秦玉平,陈一荻,王春立,王秀坤   

  1. (渤海大学信息科学与工程学院 锦州121000);(大连海事大学信息科学技术学院 大连116026);(大连理工大学计算机科学与技术学院 大连116024)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金项目(60603023),国家基础研究重大项目(973)研究专项(2001CCA00700),辽宁省教育厅重点实验室项目(LS2010180)资助。

Study on Multiclass Text Classification Algorithm Based on Hyper Ellipsoidal

QIN Yu-ping,CHEN Yi-di,WANG Chun-li,WANG Xiu-kun   

  • Online:2018-11-16 Published:2018-11-16

摘要: 提出一种基于超椭球的多类文本分类算法。对每一类样本,在特征空间求得一个包围该类尽可能多样本的最小超椭球,使得各类样本之间通过超椭球隔开。对待分类样本,通过判断其是否被超椭球包围来确定类别。实验结果表明,与超球方法相比,该方法具有较高的分类精度和分类速度。

关键词: 超椭球,多类分类,缩放因子

Abstract: A new multiclass classification algorithm based on hyper ellipsoidal was proposed. For every class, the smallest hyper ellipsoidal that contains most samples of the class was structured, which can divide the class samples from others. For the sample to be classified, its class is confirmed by the hyper ellipsoidal that it belong to. The experiment results show that the algorithm has a higher performance on classification speed and classification precision, compared with hyper sphere algorithm

Key words: Hyper ellipsoidal, Multiclass classification, Extension factor

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