Name: Between Data Science and Applied Data Analysis
ISBN: 978-3-642-18991-3

Between Data Science and Applied Data Analysis

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Editors:

Martin Schader⁰,
Wolfgang Gaul¹,
Maurizio Vichi²

Martin Schader
1. Department of Information Systems, University of Mannheim, Mannheim, Germany
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Wolfgang Gaul
1. Institute of Decision Theory, University of Karlsruhe, Karlsruhe, Germany
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Maurizio Vichi
1. Department of Statistics, University of Rome, Rome, Italy
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Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization (STUDIES CLASS)

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Table of contents (77 papers)

Front Matter

Pages I-XIII

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Clustering and Discrimination
1. Front Matter
  
  Pages 1-1
  
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2. Robust Classification Through the Forward Search
  
  Anthony Atkinson, Andrea Cerioli, Marco Riani
  
  Pages 3-12
  
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3. Fitting and Smoothing Properties of Length Constrained Smoothers Applied to Time Series
  
  Estela Bee Dagum, Alessandra Luati
  
  Pages 13-21
  
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4. Interaction Terms in Non-linear PLS via Additive Spline Transformation
  
  Jean-François Durand, Rosaria Lombardo
  
  Pages 22-29
  
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5. Discriminant Analysis With Categorical Variables: A Biplot Based Approach
  
  Sugnet Gardner, Niël le Roux
  
  Pages 30-38
  
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6. Efficient Density Clustering Using Basin Spanning Trees
  
  Sören Hader, Fred A. Hamprecht
  
  Pages 39-48
  
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7. Some Issues on Clustering of Functional Data
  
  Salvatore Ingrassia, Andrea Cerioli, Aldo Corbellini
  
  Pages 49-56
  
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8. Scalable Clustering of High Dimensional Data
  
  David Littau, Daniel Boley
  
  Pages 57-64
  
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9. Methods to Combine Classification Trees
  
  Rossella Miglio, Gabriele Soffritti
  
  Pages 65-73
  
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10. Core-Based Clustering Techniques
  
  Hans-Joachim Mucha, Hans-Georg Bartel, Jens Dolata
  
  Pages 74-82
  
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11. Combining Regression Trees and Radial Basis Function Networks in Longitudinal Data Modelling
  
  Marilena Pillati, Daniela G. Calò, Giuliano Galimberti
  
  Pages 83-91
  
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12. Implementing a new Method for Discriminant Analysis When Group Covariance Matrices are Nearly Singular
  
  Britta Pouwels, Winfried Theis, Christian Röver
  
  Pages 92-99
  
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13. Two Approaches for Discriminant Partial Least Squares
  
  Robert Sabatier, Myrtille Vivien, Pietro Amenta
  
  Pages 100-108
  
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14. Improving the Classification Performance of a Discriminant Rule by Dealing With Data Cases Having a Substantial Influence on Variable Selection
  
  Sarel Steel, Nelmarie Louw
  
  Pages 109-117
  
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15. Classification and Clustering of Vocal Performances
  
  Claus Weihs, Uwe Ligges, Jörg Güttner, Petra Hasse-Becker, Sonja Berghoff
  
  Pages 118-126
  
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16. Cluster- and Discriminant Analysis With Both Metric and Categorial Data
  
  Michael Wodny, Bernd Jäger, Karl-Ernst Biebler
  
  Pages 127-130
  
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Data Analysis and Statistics
1. Front Matter
  
  Pages 131-131
  
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2. Multivariate Mixture Models Estimation: A Genetic Algorithm Approach
  
  Roberto Baragona, Francesco Battaglia
  
  Pages 133-142
  
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3. Two-Way Clustering for Contingency Tables: Maximizing a Dependence Measure
  
  Hans-Hermann Bock
  
  Pages 143-154
  
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Keywords

Editors and Affiliations

Department of Information Systems, University of Mannheim, Mannheim, Germany

Martin Schader
Institute of Decision Theory, University of Karlsruhe, Karlsruhe, Germany

Wolfgang Gaul
Department of Statistics, University of Rome, Rome, Italy

Maurizio Vichi

Bibliographic Information

Book Title: Between Data Science and Applied Data Analysis
Book Subtitle: Proceedings of the 26th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Mannheim, July 22–24, 2002
Editors: Martin Schader, Wolfgang Gaul, Maurizio Vichi
Series Title: Studies in Classification, Data Analysis, and Knowledge Organization
DOI: https://doi.org/10.1007/978-3-642-18991-3
Publisher: Springer Berlin, Heidelberg
eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 2003
Softcover ISBN: 978-3-540-40354-8Published: 21 July 2003
eBook ISBN: 978-3-642-18991-3Published: 06 December 2012
Series ISSN: 1431-8814
Series E-ISSN: 2198-3321
Edition Number: 1
Number of Pages: XIV, 694
Number of Illustrations: 70 b/w illustrations
Topics: Database Management, Data Structures and Information Theory, Statistics for Business, Management, Economics, Finance, Insurance

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Between Data Science and Applied Data Analysis

Overview

Buy print copy

Table of contents (77 papers)

Front Matter

Clustering and Discrimination

Front Matter

Data Analysis and Statistics

Front Matter

Keywords

Editors and Affiliations

Department of Information Systems, University of Mannheim, Mannheim, Germany

Institute of Decision Theory, University of Karlsruhe, Karlsruhe, Germany

Department of Statistics, University of Rome, Rome, Italy

Bibliographic Information

Publish with us

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