FUZZY聚类分析λ最佳值的选定 |
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引用本文: | 赵成松 徐风. FUZZY聚类分析λ最佳值的选定[J]. 安徽农业科学, 1989, 0(3): 89-96 |
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作者姓名: | 赵成松 徐风 |
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作者单位: | 安徽省农科院作物研究所,安徽农学院农学系 |
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摘 要: | <正> 一、前言聚类分析(Cluster Analysis)是数值分类(Numerical Taxoaomy)学中的一个新的分支,在很多领域得到了广泛应用,特别是系统聚类法(Hierachical Clustering Methods)是目前国内外使用最多的一种方法,类与类之间的距离的不同定义产生了系统聚类的不同方法,组平均(Group—avergae or average linking)法具有空间保持和单词性,在植物遗传育种中得到卓有成效的应用。自1936年,广义距离(Generalized Distance)提出以来,人们以广义距离作为分类统计量,用Rao(1952)的中枢压缩法(Pivotal Condensation)或用
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关 键 词: | 聚类分析 植物 遗传育种 λ最佳值 |
SELECTION OF THE OPTIMUM LAMBDA IN FUZZY CLUSTER ANALYSIS |
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Abstract: | The reliability of fuzzy cluster analysis depents on the selection of lambda to a great extent. In the paper, based on 10 kinds of fuzzy cluster methods, classification was made using generalized distance discriminatory. The sum of deviation square within category and mutual information with geographical distribution for each classification were estimated. It showed that, while the sum of deviation square within category descended slowly as number of classification increasing, the value of lambda is at its best. Based on all mentioned above, the best division was made to 10 kinds of fuzzy cluster. It was got that Euclid'distance method is superior to the other. |
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