Enhanced multi-view co-clustering method with rank-based feature selection and exponential decay weighting for high dimensional data

Multi-view clustering (MVC) has gained considerable attention for its ability to integrate diverse representations of data, thereby enhancing clustering performance over traditional single-view techniques. However, constraints are still encountered including view inconsistency, high dimensionality a...

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Bibliographic Details

Main Author:	Muhammad Haris
Format:	Thesis
Language:	English
Published:	Universiti Teknologi Malaysia 2026
Subjects:	General Works::Science::Mathematics General Works::Science::Electronic computers. Computer science Sustainable Development Goals (SDG)::Industry, Innovation and Infrastructure (SDG 9)
Online Access:	https://utmik.utm.my/handle/123456789/190860
Abstract	Abstract here