Symbolic clustering using a new dissimilarity measure
Pattern Recognition
C4.5: programs for machine learning
C4.5: programs for machine learning
ACM Computing Surveys (CSUR)
Contentaddressable Memories
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values
Data Mining and Knowledge Discovery
A fuzzy k-modes algorithm for clustering categorical data
IEEE Transactions on Fuzzy Systems
Hierarchical clustering of mixed data based on distance hierarchy
Information Sciences: an International Journal
MMR: An algorithm for clustering categorical data using Rough Set Theory
Data & Knowledge Engineering
A fuzzy k-partitions model for categorical data and its comparison to the GoM model
Fuzzy Sets and Systems
On fuzzy cluster validity indices for the objects of mixed features
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
A rough set approach for selecting clustering attribute
Knowledge-Based Systems
The structural clustering and analysis of metric based on granular space
Pattern Recognition
A data labeling method for clustering categorical data
Expert Systems with Applications: An International Journal
A framework analysis for managing explicit feedback of visitors of a web site
Proceedings of the 12th International Conference on Information Integration and Web-based Applications & Services
A dissimilarity measure for the k-Modes clustering algorithm
Knowledge-Based Systems
A fuzzy k-prototype clustering algorithm for mixed numeric and categorical data
Knowledge-Based Systems
Adjusting the clustering results referencing an external set
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
Algorithm for fuzzy clustering of mixed data with numeric and categorical attributes
ICDCIT'05 Proceedings of the Second international conference on Distributed Computing and Internet Technology
Attribute value weighting in k-modes clustering
Expert Systems with Applications: An International Journal
CRUDAW: a novel fuzzy technique for clustering records following user defined attribute weights
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
| Hi-index | 0.10 |
In this paper the conventional fuzzy k-modes algorithm for clustering categorical data is extended by representing the clusters of categorical data with fuzzy centroids instead of the hard-type centroids used in the original algorithm. Use of fuzzy centroids makes it possible to fully exploit the power of fuzzy sets in representing the uncertainly in the classification of categorical data. To test the proposed approach, the proposed algorithm and two conventional algorithms (the k-modes and fuzzy k-modes algorithms) were used to cluster three categorical data sets. The proposed method was found to give markedly better clustering results.