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- W2790408076 abstract "Abstract One of the most difficult problems, in cluster analysis is the determination of the number of clusters in a data set. Solving this problem consists in detecting and finding the best number of clusters, which is an input parameter for the clustering problems. In this paper, we propose a new approach using the Maximum Stable Set Problem (MSSP) combined by Continuous Hopfield Network (CHN) to determine the number of clusters, which is a basic input parameter for K-Means method. By testing the theoretical results, the proposed approach was validated on a real application for the text mining. Some numerical examples and computational experiments assess the effectiveness of this approach as demonstrated in this paper." @default.
- W2790408076 created "2018-03-29" @default.
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- W2790408076 date "2018-01-01" @default.
- W2790408076 modified "2023-09-26" @default.
- W2790408076 title "Determining the Number of Clusters using Neural Network and Max Stable Set Problem" @default.
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- W2790408076 doi "https://doi.org/10.1016/j.procs.2018.01.093" @default.
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