计算机工程2011，Vol.37Issue(10)：162-164,3.DOI:10.3969/j.issn.1000-3428.2011.10.055
基于Fisher判别分析的贝叶斯分类器
Bayesian Classifier Based on Fisher Discriminant Analysis
曹玲玲 1潘建寿1
作者信息
- 1. 西北大学信息科学与技术学院,西安,710127
- 折叠
摘要
Abstract
Classical Bayesian classifier which satisfies the assumption of condition attributes independent of each other can not use between-class information effectively. In order to solve this problem, an improved algorithm of Bayesian classifier combined with Fisher Linear Discriminant Analysis(FLDA) is proposed. This algorithm is the key to search the projection space of maximum separation. The original samples are projected to maximum separation space and new samples are obtained. These new samples are classifed by Bayesian classifier. Experimental results show that improved Bayesian classifier has higher accuracy of classification and better performance of classification in the given data collection.关键词
贝叶斯分类器/投影变换矩阵/Fisher线性判别分析/特征向量Key words
Bayesian classifier/ projection transformation matrix/ Fisher Linear Discriminant Analysis(FLDA)/ feature vector分类
自科综合引用本文复制引用
曹玲玲,潘建寿..基于Fisher判别分析的贝叶斯分类器[J].计算机工程,2011,37(10):162-164,3.
