Cluster merging based on weighted Mahalanobis distance with application in digital mammography
A new clustering algorithm that uses a weighted Mahalanobis distance as a distance metric to perform partitional clustering is proposed. The covariance matrices of the generated clusters are used to determine cluster similarity and closeness so that clusters which are similar in shape and close in M...
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| 主要な著者: | , , , , , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English |
| 出版事項: |
IEEE
1998
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| 主題: | |
| オンライン･アクセス: | http://eprints.um.edu.my/8810/1/Cluster_merging_based_on_weighted_Mahalanobis_distance_with_application_in_digital_mammography.pdf http://eprints.um.edu.my/8810/ http://www.scopus.com/inward/record.url?eid=2-s2.0-0032306128&partnerID=40&md5=abd392ca5b0b1c59a4f056f67ba795c1 http://ieeexplore.ieee.org/xpls/absall.jsp?arnumber=710194&tag=1 |
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