Comparison of Principal Component Analysis and Multidimensional Scaling Methods for Clustering Some Honey Bee Genotypes

被引：0

作者：

Ozturk, Irfan ^{[2
]}

Orhan, Hikmet ^{[1
]}

Dogan, Zeki ^{[2
]}

机构：

[1] S Demirel Univ, Fac Agr, Dept Anim Sci, Isparta, Turkey

[2] Harran Univ, Fac Agr, Dept Anim Sci, Sanliurfa, Turkey

来源：

JOURNAL OF ANIMAL AND VETERINARY ADVANCES | 2009年 / 8卷 / 03期

关键词：

Multivariate analyses; clustering; honey bee; Apis mellifera L; k-means methods; INFERENCE;

D O I：

暂无

中图分类号：

S85 [动物医学（兽医学）];

学科分类号：

0906 ;

摘要：

The aim of this study, was to make use of Cluster Analysis, Principal Component Analysis and Multidimensional Scaling for clustering and appointments of the units to the true clusters. The honey bee genotypes (Apis mellifera L.) belonging to 30 provinces of Turkey were clustered according to Cluster Methods cited below. From these methods, McQuitty, Single Linkage, Complete Linkage, Average Linkage and Centroid Linkage showed the similar results and the results were in good agreement for separation graphics obtained by Principal Component Analysis and Multidimensional Scaling Methods while different results were found from median, centroid linkage and k-means methods.

引用

页码：413 / 419

页数：7

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