JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2010, Vol. 40 ›› Issue (5): 41-47.

• Articles • Previous Articles     Next Articles

An examination of classification model with partial least square based dimension reduction

ZENG Xue-qiang1, LI Guo-zheng2   

  1. 1. Computer Center, Nanchang University, Nanchang 330009, China;
    2. Department of Control Science and Engineering, Tongji University, Shanghai 201804, China
  • Received:2010-05-10 Online:2010-10-16 Published:2010-05-10

Abstract:

Among various methods, partial least square based dimension reduction (PLSDR) is one of the most effective one, which has been applied in many fields such as the analysis of microarray data. But the problem of choosing classification model with PLSDR has often been neglected, different classification models are applied arbitrary. Aim to this problem, an examination of different classification model with PLSDR by intensive experiments was gived.Furthermore,by using paired twotailed ttest, artificial neural network, logistic discrimination and linear support vector machine were suggested to be well performance classification models used with PLSDR.

Key words:  dimension reduction, partial least square based dimension reduction, classification model

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!