Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis

Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis

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: effect...

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Main Author: Tjhi William Chandra
Other Authors: Chen Lihui
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Computer science and engineering::Data::Data structures
Online Access:https://hdl.handle.net/10356/3503
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Institution: Nanyang Technological University
id sg-ntu-dr.10356-3503
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spelling sg-ntu-dr.10356-35032023-07-04T16:41:18Z Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis Tjhi William Chandra Chen Lihui School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Data::Data structures 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 DOCTOR OF PHILOSOPHY (EEE) 2008-09-17T09:31:08Z 2008-09-17T09:31:08Z 2008 2008 Thesis Tjhi, W. C. (2008). Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/3503 10.32657/10356/3503 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Computer science and engineering::Data::Data structures
spellingShingle DRNTU::Engineering::Computer science and engineering::Data::Data structures
Tjhi William Chandra
Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis
description 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
author2 Chen Lihui
author_facet Chen Lihui
Tjhi William Chandra
format Theses and Dissertations
author Tjhi William Chandra
author_sort Tjhi William Chandra
title Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis
title_short Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis
title_full Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis
title_fullStr Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis
title_full_unstemmed Fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis
title_sort fuzzy and possibilistic co-clustering techniques for high-dimensional data analysis
publishDate 2008
url https://hdl.handle.net/10356/3503
_version_ 1772828536513495040

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