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R: Data Analysis and Visualization by Ágnes Vidovics-Dancs, Kata Váradi, Tamás Vadász, Ágnes Tuza, Balázs Árpád Szucs, Julia Molnár, Péter Medvegyev, Balázs Márkus, István Margitai, Péter Juhász, Dániel Havran, Gergely Gabler, Barbara Dömötör, Gergely Daróczi, Ádám Banai, Milán Badics, Ferenc Illés, Edina Berlinger, Bater Makhabel, Hrishi V. Mittal, Jaynal Abedin, Brett Lantz, Tony Fischetti

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News categorization and hierarchical clustering

Hierarchical clustering divides the target dataset into multilevels or a hierarchy of clusters. It segments data points along with successive partitions.

There are two strategies for hierarchical clustering. Agglomerative clustering starts with each data object in the input dataset as a cluster, and then in the following steps, clusters are merged according to certain similarity measures that end in only one cluster. Divisive clustering, in contrast, starts with one cluster with all the data objects in the input dataset as members, and then, the cluster splits according to certain similarity measures in the following steps, and at the end, singleton clusters of individual data objects are left.

The ...

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