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Solving Non-Uniqueness in Agglomerative Hierarchical Clustering Using Multidendrograms

In agglomerative hierarchical clustering, pair-group methods suffer from a problem of non-uniqueness when two or more distances between different clusters coincide during the amalgamation process. The traditional approach for solving this drawback has been to take any arbitrary criterion in order to break ties between distances, which results in different hierarchical classifications depending on the criterion followed. In this article we propose a variable-group algorithm that consists in grouping more than two clusters at the same time when ties occur. We give a tree representation for the results of the algorithm, which we call a multidendrogram, as well as a generalization of the Lance andWilliams’ formula which enables the implementation of the algorithm in a recursive way. The authors thank A. Arenas for discussion and helpful comments. This work was partially supported by DGES of the Spanish Government Project No. FIS2006–13321–C02–02 and by a grant of Universitat Rovira i Virgili.     

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Cauchy主值积分求积公式的收敛性

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用“多化一”最小二乘法建立吸附动力学方程

用若干个一元最小二乘法，建立多元经验公式；以吸附动力学方程为例，取得了预期的结果。     

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本文给出有限和式sum from k=1 to nf(k)的积分放缩的若干结论,并讨论其在求极限、证明不等式和无穷级数收敛性等问题中的应用。     

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文章给出了Ｐａｄｅ型逼近积分形式的误差公式，并用该公式证明了Ｐａｄｅ型逼近的两个收敛定理．