• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2006, Vol. 28 ›› Issue (9): 77-79.

• 论文 • 上一篇    下一篇

定向判别分析新算法及应用

丁跃潮 万春 孙扬   

  • 出版日期:2006-09-01 发布日期:2010-05-20

  • Online:2006-09-01 Published:2010-05-20

摘要:

本文介绍了多元有序数据定向判别分析新方法的原理、建模流程、应用流程和应用实例。这种判别分析将分类建模与判别归类分开。新方法用多组或逐步判别分析对多元有序数据建模,应用时根据应用领域的知识对样本归属作初步定向,然后选择模型的相关局部进行判别归类。这种方法解决了由于时间序列多元数据周期性造成的样本分类颠倒问
问题。

关键词: 判别分析 多元数据 定向判别 建模 最优分割

Abstract:

This paper introduces the principle, modeling flowchart, application flowchart and a practical example of a new algorithm called Directional Discrimin ant Analysis (DDA), which may be used in multivariate sequence data. In DDA, class modeling and data discriminating are separated. The model for multi ivariate sequence data is built by multiple or stepwise discriminant analysis. In applying the model, the initial estimation of the samples' classifica  ation should be given according to the knowledge in the application field. Then the program selects the appropriate part of the model to discriminate th e classes of the data. In this way, we can solve the upside down problem of sample classification caused by the periodicity of multivariate time series  data.

Key words: (discriminant analysis, multivariate data, directional discriminant, modeling, best cutting)