A survey on soft subspace clustering

DOI10.1016/j.ins.2016.01.101zbMath1398.62161arXiv1409.5616OpenAlexW219179425MaRDI QIDQ1991836

Zhaohong Deng, Yizhang Jiang, Kup-Sze Choi, Jun Wang, Shi-Tong Wang

Publication date: 30 October 2018

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1409.5616

zbMATH Keywords

mixture modelsoft subspace clusteringentropy weightingfuzzy C-means/\(k\)-means modelfuzzy weighting

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Multivariate analysis and fuzziness (62H86)

Related Items (12)

Multiple kernel low-rank representation-based robust multi-view subspace clustering ⋮ Transfer learning-assisted multi-objective evolutionary clustering framework with decomposition for high-dimensional data ⋮ Robust subspace clustering based on non-convex low-rank approximation and adaptive kernel ⋮ Orthogonal self-guided similarity preserving projection for classification and clustering ⋮ Topological biclustering ARTMAP for identifying within bicluster relationships ⋮ Multi-objective soft subspace clustering in the composite kernel space ⋮ Greedy orthogonal matching pursuit for subspace clustering to improve graph connectivity ⋮ On efficient model selection for sparse hard and fuzzy center-based clustering algorithms ⋮ Robust low-rank kernel multi-view subspace clustering based on the Schatten \(p\)-norm and correntropy ⋮ Joint correntropy metric weighting and block diagonal regularizer for robust multiple kernel subspace clustering ⋮ A proximal framework for fuzzy subspace clustering ⋮ Coupled block diagonal regularization for multi-view subspace clustering

Uses Software

• COSA

Cites Work

• A feature group weighting method for subspace clustering of high-dimensional data
• A clustering ensemble framework based on elite selection of weighted clusters
• A survey on enhanced subspace clustering
• Double indices-induced FCM clustering and its integration with fuzzy subspace clustering
• Developing a feature weight self-adjustment mechanism for a K-means clustering algorithm
• Another interpretation of the EM algorithm for mixture distributions
• Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables
• Feature weighting in \(k\)-means clustering
• Optimal variable weighting for ultrametric and additive trees and \(K\)-means partitioning: Methods and software.
• Subspace clustering with automatic feature grouping
• An optimization algorithm for clustering using weighted dissimilarity measures
• A novel attribute weighting algorithm for clustering high-dimensional categorical data
• Projective clustering ensembles
• Factorial and reduced \(K\)-means reconsidered
• Comparison between two coevolutionary feature weighting algorithms in clustering
• A convergence theorem for the fuzzy subspace clustering (FSC) algorithm
• Enhanced soft subspace clustering integrating within-cluster and between-cluster information
• FUZZY CLUSTERING WITH WEIGHTING OF DATA VARIABLES
• Clustering Objects on Subsets of Attributes (with Discussion)
• Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing
• Factorial \(k\)-means analysis for two-way data.

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