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Extensions of Biplot Methodology to Discriminant Analysis

机译:将Biplot方法论扩展到判别分析

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In this paper we show how biplot methodology can be combined with various forms of discriminant analyses leading to highly informative visual displays of the respective class separations. It is demonstrated that the concept of distance as applied to discriminant analysis provides a unified approach to a wide variety of discriminant analysis procedures that can be accommodated by just changing to an appropriate distance metric. These changes in the distance metric are crucial for the construction of appropriate biplots. Several new types of biplots viz. quadratic discriminant analysis biplots for use with heteroscedastic stratified data, discriminant subspace biplots and flexible discriminant analysis biplots are derived and their use illustrated. Advantages of the proposed procedures are pointed out. Although biplot methodology is in particular well suited for complementing J > 2 classes discrimination problems its use in 2-class problems is also illustrated.
机译:在本文中,我们展示了双图方法如何与各种形式的判别分析相结合,从而导致各个类别分离的信息量很高的可视化显示。事实证明,将距离的概念应用于判别分析可为多种判别分析程序提供统一的方法,只需更改为适当的距离度量即可适应。距离度量的这些变化对于构建适当的双线图至关重要。几种新型的双刃剑。推导了用于异方差分层数据的二次判别分析双向图,判别子空间双向图和灵活判别分析双向图,并说明了它们的用法。指出了所建议程序的优点。尽管双谱图方法特别适合补充J> 2类判别问题,但也说明了在2类问题中的用法。

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