Symbolic Data Analysis and the SODAS Software
Classical statistical techniques are often inadequate when it comes to analysing some of the large and internally variable datasets common today. Symbolic Data Analysis (SDA) has evolved in response to this problem and is a vital tool for summarizing information in such a way that the resulting data is of a manageable size. Symbolic data, represented by intervals, lists, histograms, distributions, curves and the like, keeps the internal variation of summaries better than standard data. SDA therefore plays a key role in the interaction between statistics and data processing, and has established itself as an important tool for analysing officia…
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Produktdetails
Weitere Autoren: Diday, Edwin (Hrsg.)
- ISBN: 978-0-470-72355-5
- EAN: 9780470723555
- Produktnummer: 13794437
- Verlag: Wiley
- Sprache: Englisch
- Erscheinungsjahr: 2008
- Seitenangabe: 476 S.
- Plattform: PDF
- Masse: 7'396 KB
Über den Autor
Edwin Diday, Centre De Recherche en Mathématiques de la Décision, Université Paris 9, France Edwin is a Professor of Computer Science, with 50 published papers, and 14 authored or edited books to his name. He has led international research teams in Symbolic Data Analysis, and is the founder of the field. M. Noirhomme-Fraiture, Institute of Computer Science, University of Namur, Belgium Monique Noirhomme-Fraiture is Professor and Head of the Unit of Applied Mathematics at the above faculty. She is involved in several HCI projects as well as having organized conferences and workshops within this field. She has contributed to 28 published papers and co-authored 2 books.
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