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

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dc.creator ORHAN, Hikmet
dc.creator ÖZTÜRK, İRFAN
dc.creator DOĞAN, ZEKİ
dc.date 2009-02-28T22:00:00Z
dc.date.accessioned 2020-10-06T10:50:18Z
dc.date.available 2020-10-06T10:50:18Z
dc.identifier 9d7e47d3-f5a7-42f8-a625-332041ca9cda
dc.identifier https://avesis.sdu.edu.tr/publication/details/9d7e47d3-f5a7-42f8-a625-332041ca9cda/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/67577
dc.description 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.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title Comparison of Principal Component Analysis and Multidimensional Scaling Methods for Clustering Some Honey Bee Genotypes
dc.type info:eu-repo/semantics/article


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