Multi-granularity principal curves extraction based on improved spectral clustering of complex distribution data

DOI10.1016/j.ijar.2018.12.006zbMath1452.68238OpenAlexW2905427103WikidataQ115042815 ScholiaQ115042815MaRDI QIDQ1726362

Xianqiang Yang

Publication date: 20 February 2019

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2018.12.006

zbMATH Keywords

granulationcomplex dataimproved spectral clusteringmulti-granularity principal curvePL principal curves

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Reasoning under uncertainty in the context of artificial intelligence (68T37)

Cites Work

• Unnamed Item
• A multiple-valued logic approach for multigranulation rough set model
• Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic
• Double-quantitative decision-theoretic approach to multigranulation approximate space
• Efficient clustering of large uncertain graphs using neighborhood information
• Information granulation and rough set approximation
• Principal Curves
• Another look at principal curves and surfaces

This page was built for publication: Multi-granularity principal curves extraction based on improved spectral clustering of complex distribution data