Proceedings Article10.1109/FSKD.2017.8393018
Attribute weighted fuzzy clustering algorithm based on mutual information
Yao Zhu Cao,He Lin,Biao Liu +2 more
- 29 Jul 2017
- pp 1676-1682
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TL;DR: The attribute weighted fuzzy clustering algorithm based on mutual information is proposed, by using the mutual information to quantify the contribution of each attribute to the classification, the attributes are weighted and introduced into the fuzzy C mean algorithm.
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Abstract: It is studied by applying the mutual information which is used to assess the contribution of each attribute that has the different important degrees to the classification in the fuzzy clustering algorithm, then the attribute weighted fuzzy clustering algorithm based on mutual information is proposed. By using the mutual information to quantify the contribution of each attribute to the classification, the attributes are weighted and introduced into the fuzzy C mean algorithm. For incomplete data sets, the missing attribute is also introduced as a target object to be optimized and as a part of the iterative to be optimization. Finally, an example verifies the applicability of the algorithm in dealing with incomplete data sets and incomplete data sets, and analyzes the effect of each attribute value loss on clustering results in incomplete data sets.
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Citations
Particle Swarm Optimization for Traveling Salesman Problems
Peng Li
- 01 Jan 2003
TL;DR: Through presenting the concepts of swap operator and swap sequence an algorithm of a kind of special particle swarm optimization is constructed and then its application to traveling salesman problems (TSP) is proposed.
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