Statistical Data Mining and Knowledge Discovery

Hamparsum Bozdogan

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July 29, 2003 by Chapman and Hall/CRC
Reference - 624 Pages - 175 B/W Illustrations
ISBN 9781584883449 - CAT# C3448

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Features

  • Presents recent research and developments in statistical data mining
  • Reports on new models and innovative hybrid approaches useful in the analysis of large data sets
  • Identifies applications of data mining and knowledge discovery in areas such as market segmentation, image and speech analysis, and fraud detection
  • Features a chapter by Arnold Zellner on econometric and statistical data mining
  • Summary

    Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approaches that meld concepts, tools, and techniques from diverse areas, such as computer science, statistics, artificial intelligence, and financial engineering.

    Statistical Data Mining and Knowledge Discovery brings together a stellar panel of experts to discuss and disseminate recent developments in data analysis techniques for data mining and knowledge extraction. This carefully edited collection provides a practical, multidisciplinary perspective on using statistical techniques in areas such as market segmentation, customer profiling, image and speech analysis, and fraud detection. The chapter authors, who include such luminaries as Arnold Zellner, S. James Press, Stephen Fienberg, and Edward K. Wegman, present novel approaches and innovative models and relate their experiences in using data mining techniques in a wide range of applications.