A decision theoretic framework for approximating concepts
International Journal of Man-Machine Studies
Unsupervised Rough Set Classification Using GAs
Journal of Intelligent Information Systems
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
Data Analysis and Mining in Ordered Information Tables
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Interval Set Clustering of Web Users with Rough K-Means
Journal of Intelligent Information Systems
Some refinements of rough k-means clustering
Pattern Recognition
Web Intelligence and Agent Systems
ECM: An evidential version of the fuzzy c-means algorithm
Pattern Recognition
Attribute reduction in decision-theoretic rough set models
Information Sciences: an International Journal
Computing Approximations of Dominance-Based Rough Sets by Bit-Vector Encodings
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Precision of Rough Set Clustering
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Rough Cluster Quality Index Based on Decision Theory
IEEE Transactions on Knowledge and Data Engineering
Interval Set Cluster Analysis: A Re-formulation
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
A new fuzzy clustering algorithm for optimally finding granular prototypes
International Journal of Approximate Reasoning
Decision-theoretic rough set models
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Rough multi-category decision theoretic framework
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Ensemble clustering in the belief functions framework
International Journal of Approximate Reasoning
Automatically determining the number of clusters using decision-theoretic rough set
RSKT'11 Proceedings of the 6th international conference on Rough sets and knowledge technology
Fuzzy clustering with partial supervision
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
EVCLUS: evidential clustering of proximity data
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Rough–Fuzzy Collaborative Clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Possibilistic Fuzzy c-Means Clustering Algorithm
IEEE Transactions on Fuzzy Systems
Rough fuzzy MLP: knowledge encoding and classification
IEEE Transactions on Neural Networks
Autonomous Knowledge-oriented Clustering Using Decision-Theoretic Rough Set Theory
Fundamenta Informaticae - Rough Sets and Knowledge Technology (RSKT 2010)
Modelling Multi-agent Three-way Decisions with Decision-theoretic Rough Sets
Fundamenta Informaticae - Rough Sets and Knowledge Technology (RSKT 2010)
A Multiple-category Classification Approach with Decision-theoretic Rough Sets
Fundamenta Informaticae - Rough Sets and Knowledge Technology (RSKT 2010)
Soft clustering -- Fuzzy and rough approaches and their extensions and derivatives
International Journal of Approximate Reasoning
Analyzing uncertainties of probabilistic rough set regions with game-theoretic rough sets
International Journal of Approximate Reasoning
Generalized probabilistic approximations of incomplete data
International Journal of Approximate Reasoning
Incorporating logistic regression to decision-theoretic rough sets for classifications
International Journal of Approximate Reasoning
Multigranulation decision-theoretic rough sets
International Journal of Approximate Reasoning
Rule acquisition and complexity reduction in formal decision contexts
International Journal of Approximate Reasoning
Multi-class decision-theoretic rough sets
International Journal of Approximate Reasoning
An extension to Rough c-means clustering based on decision-theoretic Rough Sets model
International Journal of Approximate Reasoning
An axiomatic characterization of probabilistic rough sets
International Journal of Approximate Reasoning
On an optimization representation of decision-theoretic rough set model
International Journal of Approximate Reasoning
An automatic method to determine the number of clusters using decision-theoretic rough set
International Journal of Approximate Reasoning
Feature selection with test cost constraint
International Journal of Approximate Reasoning
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Due to their unsupervised learning nature, analyzing the semantics of clustering schemes can be difficult. Qualitative information such as preference relations may be useful in semantic analysis of clustering process. This paper describes a framework based on preference or dominance relations that helps us qualitatively analyze a clustering scheme. This qualitative interpretation is shown to be useful for combining clustering schemes that are based on different criteria. The qualitative combination can be used to analyze its quantitative counterpart and can also be used instead of the quantitative combination. The paper further extends the framework to accommodate rough set based clustering. The usefulness of the approach is illustrated using a synthetic retail database.