Advances in Classification and Data Analysis

Simone Borra

ISBN 10: 3540414886 / ISBN 13: 9783540414889

Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Feb 2001, 2001

Beschreibung

This item is printed on demand - Print on Demand Titel. Neuware -This volume contains a selection of papers presented at the biannual meeting of the Classification and Data Analysis Group of Societa Italiana di Statistica, which was held in Rome, July 5-6, 1999. From the originally submitted papers, a careful review process led to the selection of 45 papers presented in four parts as follows: CLASSIFICATION AND MULTIDIMENSIONAL SCALING Cluster analysis Discriminant analysis Proximity structures analysis and Multidimensional Scaling Genetic algorithms and neural networks MUL TIV ARIA TE DATA ANALYSIS Factorial methods Textual data analysis Regression Models for Data Analysis Nonparametric methods SPATIAL AND TIME SERIES DATA ANALYSIS Time series analysis Spatial data analysis CASE STUDIES INTERNATIONAL FEDERATION OF CLASSIFICATION SOCIETIES The International Federation of Classification Societies (IFCS) is an agency for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) from the following Scientific Societies and Groups: British Classification Society -BCS; Classification Society of North America - CSNA; Gesellschaft fUr Klassifikation - GfKI; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - CGSIS; Societe Francophone de Classification -SFC. Now the IFCS includes also the following Societies: Dutch-Belgian Classification Society - VOC; Polish Classification Society -SKAD; Associayao Portuguesa de Classificayao e Analise de Dados -CLAD; Korean Classification Society -KCS; Group-at-Large.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 392 pp. Englisch.

Bestandsnummer des Verkäufers 9783540414889

Bibliografische Details

• Titel: Advances in Classification and Data Analysis
• Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Feb 2001
• Erscheinungsjahr: 2001
• Sprache: Englisch
• ISBN-10: 3540414886
• ISBN-13: 9783540414889
• Einband: Taschenbuch
• Zustand: Neu
• Abmessungen: 235B x 155 H x 22 T Millimeter Breite: 235 mm, Höhe: 155 mm, Tiefe: 22 mm
• Gewicht: 593 Gramm

Über diesen Titel

Inhaltsangabe

This volume contains a selection of papers presented at the biannual meeting of the Classification and Data Analysis Group of Societa Italiana di Statistica, which was held in Rome, July 5-6, 1999. From the originally submitted papers, a careful review process led to the selection of 45 papers presented in four parts as follows: CLASSIFICATION AND MULTIDIMENSIONAL SCALING Cluster analysis Discriminant analysis Proximity structures analysis and Multidimensional Scaling Genetic algorithms and neural networks MUL TIV ARIA TE DATA ANALYSIS Factorial methods Textual data analysis Regression Models for Data Analysis Nonparametric methods SPATIAL AND TIME SERIES DATA ANALYSIS Time series analysis Spatial data analysis CASE STUDIES INTERNATIONAL FEDERATION OF CLASSIFICATION SOCIETIES The International Federation of Classification Societies (IFCS) is an agency for the dissemination of technical and scientific information concerning classification and data analysis in the broad sense and in as wide a range of applications as possible; founded in 1985 in Cambridge (UK) from the following Scientific Societies and Groups: British Classification Society -BCS; Classification Society of North America - CSNA; Gesellschaft fUr Klassifikation - GfKI; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - CGSIS; Societe Francophone de Classification -SFC. Now the IFCS includes also the following Societies: Dutch-Belgian Classification Society - VOC; Polish Classification Society -SKAD; Associayao Portuguesa de Classificayao e Analise de Dados -CLAD; Korean Classification Society -KCS; Group-at-Large.