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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
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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