Advances in Data Science and Classification de Alfredo Rizzi

Advances in Data Science and Classification: Proceedings of the 6th Conference of the International Federation of Classification Societies (IFCS-98) Università “La Sapienza”, Rome, 21–24 July, 1998: Studies in Classification, Data Analysis, and Knowledge Organization

Alfredo Rizzi

Maurizio Vichi

Hans-Hermann Bock

en Limba Engleză Paperback – 10 iul 1998

International Federation of Classification Societies The International Federation of Classification Societies (lFCS) is an agency for the dissemination of technical and scientific information concerning classification and multivariate data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) by the following Scientific Societies and Groups: - British Classification Society - BCS - Classification Society of North America - CSNA - Gesellschaft fUr Klassification - GfKI - Japanese Classification Society - JCS - Classification Group ofItalian Statistical Society - CGSIS - Societe Francophone de Classification - SFC Now the IFCS includes also the following Societies: - Dutch-Belgian Classification Society - VOC - Polish Classification Section - SKAD - Portuguese Classification Association - CLAD - Group at Large - Korean Classification Society - KCS IFCS-98, the Sixth Conference of the International Federation of Classification Societies, was held in Rome, from July 21 to 24, 1998. Five preceding conferences were held in Aachen (Germany), Charlottesville (USA), Edinburgh (UK), Paris (France), Kobe (Japan).

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Specificații

ISBN-13: 9783540646419
ISBN-10: 3540646418
Pagini: 700
Ilustrații: XV, 682 p. 9 illus.
Dimensiuni: 155 x 235 x 37 mm
Greutate: 0.96 kg
Ediția:Softcover reprint of the original 1st ed. 1998
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Studies in Classification, Data Analysis, and Knowledge Organization

Locul publicării:Berlin, Heidelberg, Germany

Cuprins

I: Methodologies in Classification.- II: Other Approaches for Classification: Discrimination, Neural Network, Regression Trees.- III: Factorial Methods.- IV: Symbolic and Textual Data Analysis.- V: Multivariate and Multidimensional Data Analysis.- VI: Case Studies.- Contributors Index.- Key Words Index.- Conference Committee.- List of Reviewers.