An Optimal Hierarchically Clustering Number Determining Method ?
نویسندگان
چکیده
In the hierarchical clustering algorithms, it has become a basic difficult problem to determine the optimal clustering number in the dataset, as a result of the influence of outliers and noise points. Therefore, we propose a method to remove these interferential data in two stages in the hierarchical clustering algorithm, which is based on the traditional noise data removal method. Furthermore, we can obtain the optimal number of clusters. Theoretical analysis and experimental results have verified the effectiveness and good performance of the algorithm.
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