A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
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)
Rough set algorithms in classification problem
Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
When Is ''Nearest Neighbor'' Meaningful?
ICDT '99 Proceedings of the 7th International Conference on Database Theory
A Rough Set-Aided System for Sorting WWW Bookmarks
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
Feature Selection for Clustering - A Filter Solution
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
SCHISM: A New Approach for Interesting Subspace Mining
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
A Generic Framework for Efficient Subspace Clustering of High-Dimensional Data
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Cluster Analysis for Data Mining and System Identification
Cluster Analysis for Data Mining and System Identification
A convergence theorem for the fuzzy subspace clustering (FSC) algorithm
Pattern Recognition
DUSC: Dimensionality Unbiased Subspace Clustering
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
EDSC: efficient density-based subspace clustering
Proceedings of the 17th ACM conference on Information and knowledge management
Computational Intelligence: Methods and Techniques
Computational Intelligence: Methods and Techniques
Rough Sets and Functional Dependencies in Data: Foundations of Association Reducts
Transactions on Computational Science V
Rough Entropy Based k-Means Clustering
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Applications of rough set based K-means, Kohonen SOM, GA clustering
Transactions on rough sets VII
Rough feature selection for intelligent classifiers
Transactions on rough sets VII
Clustering ensemble for unsupervised feature selection
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Evolutionary rough k-medoid clustering
Transactions on rough sets VIII
A fuzzy subspace algorithm for clustering high dimensional data
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Association reducts: a framework for mining multi-attribute dependencies
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Rough–Fuzzy Collaborative Clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Survey of clustering algorithms
IEEE Transactions on Neural Networks
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Fuzzy techniques have been used for handling vague boundaries of arbitrarily oriented clusters. However, traditional clustering algorithms tend to break down in high dimensional spaces due to inherent sparsity of data. We propose a modification in the objective function of Gustafson-Kessel clustering algorithm for projected clustering and prove the convergence of the resulting algorithm. We present the results of applying the proposed projected Gustafson-Kessel clustering algorithm to synthetic and UCI data sets, and also suggest a way of extending it to a rough set based algorithm.