Classification and Data Analysis

1. Front Matter

   Pages I-X

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2. Classification

   1. Front Matter

      Pages 1-1

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   2. Methodologies in Classification

      1. Measuring the Influence of Individual Observations and Variables in Cluster Analysis

         • Andrea Cerioli

         Pages 3-10

      2. Consensus Classification for A Set of Multiple Time Series

         • Pierpaolo D’Urso, Maria Grazia Pittau

         Pages 11-18

      3. A Bootstrap Method for Adaptive Cluster Sampling

         • Tonio Di Battista, Domenico Di Spalatro

         Pages 19-26

      4. Forecasting a Classification

         • Domenica Fioredistella Iezzi, Maurizio Vichi

         Pages 27-34

   3. Fuzzy Clustering and Fuzzy Methods

      1. Neural Networks as a Fuzzy Semantic Network of Events

         • Antonio Bellacicco

         Pages 35-41

      2. Hierarchical Fuzzy Clustering: An Example of Spatio-Temporal Analysis

         • Loredana Cerbara

         Pages 43-48

      3. A New Algorithm for Semi-Fuzzy Clustering

         • Giampaolo Iacovacci

         Pages 49-54

      4. Fuzzy Classification and Hyperstructures: An Application to Evaluation of Urban Projects

         • Antonio Maturo, Barbara Ferri

         Pages 55-62

      5. Variable Selection In Fuzzy Clustering

         • Maria Adele Milioli

         Pages 63-70

3. Other Approaches for Classification

   1. Front Matter

      Pages 71-71

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   2. Discrimination and Classification

      1. Discriminant Analysis Using Markovian Automodels

         • Marco Alfò, Paolo Postiglione

         Pages 73-80

      2. Discretization of Continuous-Valued Data in Symbolic Classification Learning

         • F. Esposito, D. Malerba, G. Semeraro, S. Caggese

         Pages 81-88

      3. Logistic Discrimination by Kullback-Leibler type Distance Measures

         • Salvatore Ingrassia

         Pages 89-96

      4. An Empirical Discrimination Algorithm based on Projection Pursuit Density Estimation

         • Angela Montanari, Daniela G. Calò

         Pages 97-104

   3. Regression Tree and Neural Networks

      1. Notes on Methods for Improving Unstable Classifiers

         • Rossella Miglio, Marilena Pillati

         Pages 105-112

      2. Selection of Cut Points in Generalized Additive Models

         • Francesco Mola

         Pages 113-120

      3. Latent Budget Trees for Multiple Classification

         • Roberta Siciliano

         Pages 121-128

4. Multivariate and Multidimensional Data Analysis

   1. Front Matter

      Pages 129-129

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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 -GfKl; Japanese Classification Society -JCS; Classification Group of Italian Statistical Society - COSIS; Societe Francophone de Classification -SFC. Now the IFCS includes the following Societies: Dutch-Belgian Classification Society - VOC; Polish Classification Section - SKAD; Portuguese Classification Association - CLAD; Group-at-Large; Korean Classification Society -KCS. Biannual Meeting of the Classification and Data Analysis Group of SIS The biannual meeting of the Classification and Data Analysis Group of Societa Italiana di Statistica (SIS) was held in Pescara, July 3 -4, 1997. The 69 papers presented were divided in 17 sessions. Each session was organized by a chairperson with two invited speakers and two contributed papers from a call for papers. All the works were referred. Furthermore, during the meeting a discussant was provided for each session. A short version of the papers (4 pages) was.published before the conference.

• Classification
• Clustering
• Datenanalyse
• Factor analysis
• Klassifikation
• Projection Pursuit
• Regression analysis
• Time series
• Variance
• cluster analysis
• coding
• data analysis
• multidimensional scaling

• Dipartimento Metodi Quantitativi e Teoria Economica, University “G. D’Annunzio” di Chieti, Pescara, Italy

  Maurizio Vichi

• Lehrstuhl für Mathematische Methoden der Wirtschaftswissenschaften, University of Augsburg, Augsburg, Germany

  Otto Opitz

Policies and ethics