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...
| Main Author: | Muhammad Haris |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
Universiti Teknologi Malaysia
2026
|
| Subjects: | |
| Online Access: | https://utmik.utm.my/handle/123456789/190860 |
| Abstract | Abstract here |
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