Robust local triangular kernel density-based clustering for high-dimensional data
A number of clustering algorithms can be employed to find clusters in multivariate data. However, the effectiveness and efficiency of the existing algorithms are limited, since the respective data has high dimension, contain large amount of noise and consist of clusters with arbitrary shapes and den...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/51289/ http://apps.webofknowledge.com.ezproxy.utm.my/full_record.do?product=WOS&search_mode=GeneralSearch&qid=11&SID=R2Cjh3fA6kIeWhVr585&page=1&doc=1 |
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| Institution: | Universiti Teknologi Malaysia |