バイオメディカル・ファジィ・システム学会大会講演論文集
Online ISSN : 2424-2586
Print ISSN : 1345-1510
ISSN-L : 1345-1510
34
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主成分分析を用いた集団のグルーピング
中野 正博
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会議録・要旨集 フリー

p. 3-6-

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This paper proposed a new method of grouping after principal component analysis. First, we argued that normalized principal component scores should be used in order to compare many results with each other. Using these scores, we also proposed two ways in grouping of the members in two-dimensional maps: box plots and ellipse plots. This method is an excellent way to classify all people according to their tendencies or to select extreme people based on rules. The advantage of this method is that no one is left out in the classification. Also, the percentage can be freely decided, and the classification is calculated automatically. The nine classified areas can be given meaning.

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