Gradient-Based FCM and a neural network for clustering of incomplete data

Authors:
Dong-Chul Park
Affiliations:
Intelligent Computing Research Lab., Dept. of Information Engineering, Myong Ji University, Korea
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
Year:
2005

Citing 2
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Pattern recognition using neural networks: theory and algorithms for engineers and scientists

Pattern recognition using neural networks: theory and algorithms for engineers and scientists
Fuzzy c-means clustering of incomplete data

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

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Abstract

Clustering of incomplete data using a neural network and the Gradient-Based Fuzzy c-Means (GBFCM) is proposed in this paper. The proposed algorithm is applied to the Iris data to evaluate its performance. When compared with the existing Optimal Completion Strategy FCM (OCSFCM), the proposed algorithm shows 18%-20% improvement of performance over the OCSFCM.