A Comparative Study on Vector-based and Matrix-based Linear Discriminant Analysis

Bo Yang1; Ying-yong Bu2

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A Comparative Study on Vector-based and Matrix-based Linear Discriminant Analysis

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—Recently a kind of matrix-based discriminantfeature extraction approach called 2DLDA have been drawnmuch attention by researchers. 2DLDA can avoid thesingularity problem and has low computational costs and hasbeen experimentally reported that 2DLDA outperformstraditional LDA. In this paper, we compare 2DLDA withLDA in view of the discriminant power and find that 2DLDAas a kind of special LDA has no stronger discriminant powerthan LDA. So, why 2DLDA outperforms LDA in some cases?Through theoretical analysis, we find it is mainly because ofthe difference of stability under nonsingular lineartransformation and linear operation power between 2DLDAand LDA. In experimental parts, the results of experimentsgive enough proof on our claims and show in some cases theperformance of 2DLDA will be possible superior to that ofLDA and in other cases the performance of LDA will bepossible superior to that of 2DLDA.

机译：- 特别是一种称为2DLDA的基于基于基于矩阵的歧视性提取方法，研究人员被提出了注意。 2DLDA可以避免表格问题，并且计算成本低，并且实验报告了2DLDA超级形象的LDA。在本文中，我们鉴于判别权力，比较2DLDA与判别权力，发现2DLDAAS一种特殊的LDA没有更强大的判别动力。所以，为什么2DLDA优于LDA在某些情况下？通过理论分析，我们发现它主要是因为在2DLDA和LDA之间的非垂直线性交流和线性操作功率下的稳定性差异。在实验零件中，实验的结果足够证明我们的索赔和在某些情况下表现出2DLDA的表现，可以优于oomlda和其他情况，在其他情况下，LDA的性能将放在2dlda的表现。

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《Journal of Computers》 |2011年第4期|共7页
作者
Bo Yang1; Ying-yong Bu2;
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A Comparative Study on Vector-based and Matrix-based Linear Discriminant Analysis

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