A random finite set model for data clustering
The goal of data clustering is to partition data points into groups to optimize a given objective function. While most existing clustering algorithms treat each data point as vector, in many applications each datum is not a vector but a point pattern or a set of points. Moreover, many existing clust...
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| Format: | Conference Paper |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2014
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| Online Access: | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6916264&action=search&sortType=&rowsPerPage=&searchField=Search_All&matchBoolean=true&queryText=((A%20random%20finite%20set%20model%20for%20data%20clustering)%20AND%20phung) http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6916264&action=search&sortType=&rowsPerPage=&searchField=Search_All&matchBoolean=true&queryText=((A%20random%20finite%20set%20model%20for%20data%20clustering)%20AND%20phung) http://hdl.handle.net/20.500.11937/25019 |
Internet
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6916264&action=search&sortType=&rowsPerPage=&searchField=Search_All&matchBoolean=true&queryText=((A%20random%20finite%20set%20model%20for%20data%20clustering)%20AND%20phung)http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6916264&action=search&sortType=&rowsPerPage=&searchField=Search_All&matchBoolean=true&queryText=((A%20random%20finite%20set%20model%20for%20data%20clustering)%20AND%20phung)
http://hdl.handle.net/20.500.11937/25019