Clustering using PK-D: A connectivity and density dissimilarity
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- 作者：Ariel E. Bayá ; ; baya@cifasis-conicet.gov.ar" class="auth_mail" title="E-mail the corresponding author ; Mó ; nica G. Larese larese@cifasis-conicet.gov.ar" class="auth_mail" title="E-mail the corresponding author ; Pablo M. Granitto granitto@cifasis-conicet.gov.ar" class="auth_mail" title="E-mail the corresponding author
- 关键词：Clustering ; Dimensionality reduction
- 刊名：Expert Systems with Applications
- 出版年：2016
- 出版时间：1 June 2016
- 年：2016
- 卷：51
- 期：Complete
- 页码：151-160
- 全文大小：1626 K
文摘
- •
ara0001">New dissimilarity joining connectivity and density information.
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ara0002">Clustering using low vector space representation based on the new dissimilarity.
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ara0003">Interesting clustering application using gene expression and image data.
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ara0004">Improved clustering quality of simple algorithms like k-means.