Bozdogan H. (ed.) Statistical Data Mining and Knowledge Discovery

Chapman&Hall/CRC, 2004 — 595 p.
ISBN: 1-58488-344-8This book contains a collection of selected representative papers of the thematic areas covered during the International Conference on Statistical Data Mining and Knowledge Discovery took place during June 22-25, 2002, including some of the keynote lectures. It is with regret that Usama Fayyad and Naeem Hashmi could not make a contribution to this volume as the keynote speakers. I am grateful and extend my sincere thanks to all the contributors to this volume, the Session Organizers and Chairs. All the submitted papers were reviewed and put in the format of Chapman & Hall/CRC book style. As the editor, I am ultimately responsible for any inadvertent errors or omissions.The Role of Bayesian and Frequentist Multivariate Modeling in Statistical Data Mining – S. James Press
Intelligent Statistical Data Mining with Information Complexity and Genetic Algorithms – Hamparsum Bozdogan
Econometric and Statistical Data Mining, Prediction and Policy-Making – Arnold Zellner
Data Mining Strategies for the Detection of Chemical Warfare Agents – Jeffrey. L. Solka, Edward J. Wegman, and David J. Marchette
Disclosure Limitation Methods Based on Bounds for Large Contingency Tables With Applications to Disability – Adrian Dobra, Elena A. Erosheva and Stephen E. Fienberg
Partial Membership Models with Application to Disability Survey Data – Elena A. Erosheva
Automated Scoring of Polygraph Data – Aleksandra B. Slavkovic
Missing Value Algorithms in Decision Trees – Hyunjoong Kim and Sumer Yates
Unsupervised Learning from Incomplete Data Using a Mixture Model Approach – Lynette Hunt and Murray Jorgensen
Improving the Performance of Radial Basis Function (RBF) Classification Using Information Criteria – Zhenqiu Liu and Hamparsum Bozdogan
Use of Kernel-Based Techniques for Sensor Validation in Nuclear Power Plants – Andrei V. Gribok, Aleksey M. Urmanov, J. Wesley Hines, and Robert E. Uhrig
Data Mining and Traditional Regression – Christopher M. Hill, Linda C. Malone, and Linda Trocine
An Extended Sliced Inverse Regression – Masahiro Mizuta
Using Genetic Programming to Improve the Group Method of Data Handling in Time Series Prediction – M. Hiassat, M.F. Abbod, and N. Mort
Data Mining for Monitoring Plant Devices Using GMDH and Pattern Classification – B.R. Upadhyaya and B. Lu
Statistical Modeling and Data Mining to Identify Consumer Preferences – Francois Boussu
and Jean Jacques Denimal
Testing for Structural Change Over Time of Brand Attribute Perceptions in Market Segments – Sara Dolnicar and Friedrich Leisch
Testing for Structural Change Over Time of Brand Attribute Perceptions in Market Segments – Sara Dolnicar and Friedrich Leisch
Global Principal Component Analysis for Dimensionality Reduction in Distributed Data Mining – Hairong Qi, Tse-Wei Wang, and J. Douglas Birdwell
A New Metric for Categorical Data – S. H. Al-Harbi, G. P. McKeown and V. J. Rayward-Smith
Ordinal Logistic Modeling Using ICOMP as a Goodness-of-Fit Criterion – J. Michael Lanning and Hamparsum Bozdogan
Comparing Latent Class Factor Analysis with the Traditional Approach in Data Mining – Jay Magidson and Jeroen Vermunt
On Cluster Effects in Mining Complex Econometric Data – M. Ishaq Bhatti
Neural Network-Based Data Mining Techniques for Steel Making – Ravindra K. Sarma, Amar Gupta, and Sanjeev Vadhavkar
Solving Data Clustering Problem as a String Search Problem – V. Olman, D. Xu, and Y. Xu
Behavior-Based Recommender Systems as Value-Added Services for Scientific Libraries – Andreas Geyer-Schulz, Michael Hahsler, Andreas Neumann, and Anke Thede
GTP (General Text Parser) Software for Text Mining – Justin T. Giles, Ling Wo, and Michael W. Berry
Implication Intensity: From the Basic Statistical Definition to the Entropic Version – Julien Blanchard, Pascale Kuntz, Fabrice Guillet, and Regis Gras
Use of a Secondary Splitting Criterion in Classification Forest Construction – Chang-Yung Yu and Heping Zhang
A Method Integrating Self-Organizing Maps to Predict the Probability of Barrier Removal – Zhicheng Zhang and Fr´ed´eric Vanderhaegen
Cluster Analysis of Imputed Financial Data Using an Augmentation-Based Algorithm – H. Bensmail and R. P. DeGennaro
Data Mining in Federal Agencies – David L. Banks and Robert T. Olszewski
STING: Evaluation of Scientific & Technological Innovation and Progress – S. Sirmakessis, K. Markellos, P. Markellou, G. Mayritsakis, K. Perdikouri, A. Tsakalidis, and Georgia Panagopoulou
The Semantic Conference Organizer – Kevin Heinrich, Michael W. Berry, Jack J. Dongarra, and Sathish Vadhiyar