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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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Automatic abstraction of document texts and the k-medoids algorithm

The k-medoids algorithm is extended from the k-means algorithm to decrease the sensitivity to the outlier data points.

Given the dataset D and the predefined parameter k, the k-medoids algorithm or the PAM algorithm can be described as shown in the upcoming paragraphs.

As per a clustering related to a set of k medoids, the quality is measured by the average distance between the members in each cluster and the corresponding representative or medoids.

An arbitrary selection of k objects from the initial dataset of objects is the first step to find the k medoids. In each step, for a selected object and a nonselected node , if the quality of the cluster is improved as a result of swapping ...

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