Unified Multi-view Data Clustering: Simultaneous Learning of Consensus Coefficient Matrix and Similarity Graph

Integrating data from multiple sources or views has become increasingly common in data analysis, particularly in fields like healthcare, finance, and social sciences. However, clustering such multi-view data poses unique challenges due to the heterogeneity and complexity of the data sources. Traditi...

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Vydáno v:	Cognitive computation Ročník 17; číslo 1; s. 38
Hlavní autoři:	Dornaika, F., El Hajjar, S., Charafeddine, J., Barrena, N.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.02.2025 Springer Nature B.V Springer
Témata:	Algorithms Artificial Intelligence Biotechnology Clustering Cognitive science Computation by Abstract Devices Computational Biology/Bioinformatics Computer Science Correspondence Data analysis Datasets Graphical representations Heterogeneity Impact analysis Learning Machine learning Methods Optimization Parameters Performance evaluation Regularization Robustness Sensitivity analysis Similarity Tuning Data fusion Spectral embedding Graph-based multi-view clustering Unified and consensus graph learning Soft cluster assignments
ISSN:	1866-9956, 1866-9964
On-line přístup:	Získat plný text
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