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Data Analysis in Bi-partial Perspective: Clustering and Beyond

Produktform: E-Buch Text Elektronisches Buch in proprietärem

This procedure has a striking affinity with the classical hierarchical merger algorithms, while also incorporating the stopping rule, based on the objective function. The approach resolves the cluster number issue, as the solutions obtained include both the content and the number of clusters. Further, it is demonstrated how the bi-partial principle can be effectively applied to a wide variety of problems in data analysis.The book offers a valuable resource for all data scientists who wish to broaden their perspective on basic approaches and essential problems, and to thus find answers to questions that are often overlooked or have yet to be solved convincingly. It is also intended for graduate students in the computer and data sciences, and will complement their knowledge and skills with fresh insights on problems that are otherwise treated in the standard “academic” manner. weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Elektronisches Format: PDF

Sprache(n): Englisch

ISBN: 978-3-030-13389-4 / 978-3030133894 / 9783030133894

Verlag: Springer International Publishing

Erscheinungsdatum: 23.03.2019

Seiten: 153

Autor(en): Jan W. Owsiński

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