Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Fast algorithms for projected clustering
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
ACM Computing Surveys (CSUR)
FREM: fast and robust EM clustering for large data sets
Proceedings of the eleventh international conference on Information and knowledge management
Clustering For Data Mining: A Data Recovery Approach (Chapman & Hall/Crc Computer Science)
Clustering For Data Mining: A Data Recovery Approach (Chapman & Hall/Crc Computer Science)
Convergence Theorems for Generalized Alternating Minimization Procedures
The Journal of Machine Learning Research
Data Clustering: Theory, Algorithms, and Applications (ASA-SIAM Series on Statistics and Applied Probability)
A fuzzy subspace algorithm for clustering high dimensional data
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
A survey of fuzzy clustering algorithms for pattern recognition. I
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A survey of fuzzy clustering algorithms for pattern recognition. II
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A fuzzy k-modes algorithm for clustering categorical data
IEEE Transactions on Fuzzy Systems
A Convergence Theorem for the Fuzzy ISODATA Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust relief-feature weighting, margin maximization, and fuzzy optimization
IEEE Transactions on Fuzzy Systems
Projected Gustafson-Kessel clustering algorithm and its convergence
Transactions on rough sets XIV
Feature interaction in subspace clustering using the Choquet integral
Pattern Recognition
Partitive clustering (K-means family)
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
A New Locally Weighted K-Means for Cancer-Aided Microarray Data Analysis
Journal of Medical Systems
Fuzzy partition based soft subspace clustering and its applications in high dimensional data
Information Sciences: an International Journal
Evolving soft subspace clustering
Applied Soft Computing
Hi-index | 0.01 |
We establish the convergence of the fuzzy subspace clustering (FSC) algorithm by applying Zangwill's convergence theorem. We show that the iteration sequence produced by the FSC algorithm terminates at a point in the solution set S or there is a subsequence converging to a point in S. In addition, we present experimental results that illustrate the convergence properties of the FSC algorithm in various scenarios.