Variable precision rough set model
Journal of Computer and System Sciences
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications
Algorithms for Fuzzy Clustering: Methods in c-Means Clustering with Applications
Variable precision rough set approach to multiple decision tables
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
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In order to analyze the distribution of mind-sets (collections of evaluations) in a group, a hierarchical clustering of decision tables has been examined. By the method, we know clusters of mind-set but the clusters are not always optimal in some criterion. In this paper, we develop non-hierarchical clustering techniques for decision tables. In order to treat positive and negative evaluations to a common profile, we use a vector of rough membership values to represent individual opinion to a profile. Using rough membership values, we develop a K-means method as well as fuzzy c-means methods for clustering decision tables. We examined the proposed methods in clustering real world decision tables.