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基于概率类和不相关判别的半监督局部Fisher方法

DOI: 10.13195/j.kzyjc.2013.1673, PP. 32-38

Keywords: Fisher,判别分析,维数约简,概率类,不相关判别,半监督学习

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Abstract:

Fisher判别分析是统计模式识别中经典的有监督维数约简方法,可以在最大化类间散度的同时最小化类内散度,但存在分析过程中仅使用有标记数据而忽略无标记数据的问题.鉴于此,提出基于概率类和不相关判别的半监督局部Fisher(SLFisher)方法,以实现半监督学习的高维映射到低维的类间数据对尽可能地分离,且类内邻近数据尽可能地紧凑.采用2组标准数据集进行实验,结果表明了SLFisher方法能够有效提高识别率.

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