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|Title:||Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis||Authors:||Tjhi William Chandra||Keywords:||DRNTU::Engineering::Computer science and engineering::Data::Data structures||Issue Date:||2008||Source:||Tjhi, W. C. (2008). Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||A study and development of a new data clustering framework called Fuzzy-possibilistic Co-clustering, which is formulated based on the hybrid of fuzzy clustering, possibilistic clustering, and co-clustering; with the objective of achieving simultaneously several goals of data analysis, namely: effective clustering of high-dimensional data, rich and natural representations of clusters, robustness to outliers, and highly-interpretable clusters||URI:||https://hdl.handle.net/10356/3503||DOI:||10.32657/10356/3503||Rights:||Nanyang Technological University||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Theses|
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