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A Quantitative Discriminant Method of Elbow Point for the Optimal Number of Clusters in Clustering Algorithm

机译：聚类算法中最佳簇数的弯头点定量判别方法

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Congming Shi; Bingtao Wei; Shoulin Wei; Wen Wang; Hai Liu; Jialei Liu;
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5. Scalable clustering algorithms and optimization methods for parallel architectures. [D] . Khlopotine, Andrei B. 2015

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6. Does Determination of Initial Cluster Centroids Improve the Performance of K-Means Clustering Algorithm? Comparison of Three Hybrid Methods by Genetic Algorithm Minimum Spanning Tree and Hierarchical Clustering in an Applied Study [O] . Saeedeh Pourahmad, Atefeh Basirat, Amir Rahimi, 2020

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8. Rank Correlation Coefficients as Optimality Measures for Ordinal Cluster Methods [R] . Janowitz, M. F. 1981

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A Quantitative Discriminant Method of Elbow Point for the Optimal Number of Clusters in Clustering Algorithm

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