Classification and Data Mining

1. Front Matter

   Pages i-xiv

   PDF

2. Classification and Data Analysis

   1. Front Matter

      Pages 1-1

      PDF

   2. Robust Random Effects Models: A Diagnostic Approach Based on the Forward Search

      • Bruno Bertaccini, Roberta Varriale

      Pages 3-10

   3. Joint Correspondence Analysis Versus Multiple Correspondence Analysis: A Solution to an Undetected Problem

      • Sergio Camiz, Gastão Coelho Gomes

      Pages 11-18

   4. Inference on the CUB Model: An MCMC Approach

      • Laura Deldossi, Roberta Paroli

      Pages 19-26

   5. Robustness Versus Consistency in Ill-Posed Classification and Regression Problems

      • Robert Hable, Andreas Christmann

      Pages 27-35

   6. Issues on Clustering and Data Gridding

      • Jukka Heikkonen, Domenico Perrotta, Marco Riani, Francesca Torti

      Pages 37-44

   7. Dynamic Data Analysis of Evolving Association Patterns

      • Alfonso Iodice D’Enza, Francesco Palumbo

      Pages 45-53

   8. Classification of Data Chunks Using Proximal Vector Machines and Singular Value Decomposition

      • Antonio Irpino, Mario Rosario Guarracino, Rosanna Verde

      Pages 55-62

   9. Correspondence Analysis in the Case of Outliers

      • Anna Langovaya, Sonja Kuhnt, Hamdi Chouikha

      Pages 63-70

   10. Variable Selection in Cluster Analysis: An Approach Based on a New Index

       • Isabella Morlini, Sergio Zani

       Pages 71-79

   11. A Model for the Clustering of Variables Taking into Account External Data

       • Karin Sahmer

       Pages 81-88

   12. Calibration with Spatial Data Constraints

       • Ivan Arcangelo Sciascia

       Pages 89-94

3. Data Mining

   1. Front Matter

      Pages 95-95

      PDF

   2. Clustering Data Streams by On-Line Proximity Updating

      • Antonio Balzanella, Yves Lechevallier, Rosanna Verde

      Pages 97-104

   3. Summarizing and Detecting Structural Drifts from Multiple Data Streams

      • Antonio Balzanella, Rosanna Verde

      Pages 105-112

   4. A Model-Based Approach for Qualitative Assessment in Opinion Mining

      • Maria Iannario, Domenico Piccolo

      Pages 113-120

   5. An Evaluation Measure for Learning from Imbalanced Data Based on Asymmetric Beta Distribution

      • Nguyen Thai-Nghe, Zeno Gantner, Lars Schmidt-Thieme

      Pages 121-129

   6. Outlier Detection for Geostatistical Functional Data: An Application to Sensor Data

      • Elvira Romano, Jorge Mateu

      Pages 131-138

   7. Graphical Models for Eliciting Structural Information

      • Federico M. Stefanini

      Pages 139-146

​​​​​​​​​This volume contains both methodological papers showing new original methods, and papers on applications illustrating how new domain-specific knowledge can be made available from data by clever use of data analysis methods. The volume is subdivided in three parts: Classification and Data Analysis; Data Mining; and Applications. The selection of peer reviewed papers had been presented at a meeting of classification societies held in Florence, Italy, in the area of "Classification and Data Mining".​

• Classification
• Data Analysis
• Data Mining

• Department of Statistics, Università degli Studi di Firenze, Firenze, Italy

  Antonio Giusti

• Fakultät für Informatik, und Mathematik, Universität Passau, Passau, Germany

  Gunter Ritter

• Sapienza", Department of Statistics, University of Rome "La, Rome, Italy

  Maurizio Vichi

Policies and ethics