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Statistical Analysis of Massive Data Streams: Proceedings of a Workshop (2004)

Chapter: John Elder Ensembles of Models: Simplicity (of Function) Through Complexity (of Form)

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Suggested Citation:"John Elder Ensembles of Models: Simplicity (of Function) Through Complexity (of Form) ." National Research Council. 2004. Statistical Analysis of Massive Data Streams: Proceedings of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/11098.
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Page 190

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ENSEMBLES OF MODELS: SIMPLICITY (OF FUNCTION) THROUGH COMPLEXITY (OF FORM) 190 John Elder Ensembles of Models: Simplicity (of Function) Through Complexity (of Form) Transcript of Presentation and PDF Slides BIOSKETCH: John Elder is chief scientist of Elder Research, Inc. (ERI), a consulting firm with offices in Charlottesville, Virginia, and Washington, D.C. (www.datamininglab.com). Dr. Elder earned electrical engineering degrees from Rice University and a PhD in systems engineering from the University of Virginia, where he is currently an adjunct professor, teaching optimization. He spent 5 years in high-tech defense consulting, 4 years heading research at an investment management firm, 2 years in Rice University's Computational and Applied Mathematics Department, and has led ERI since 1995. Since 1995, Dr. Elder has led ERI's projects in credit scoring, direct marketing, sales forecasting, stock selection, image pattern recognition, drug efficacy estimation, volatility forecasting, fraud detection, biometrics, and market timing. He writes and speaks widely on pattern discovery techniques and is active on statistical and engineering journals and boards. Dr. Elder is active in statistics and engineering conferences and boards and is a program co-chair of the 2004 Knowledge Discovery and Data Mining Conference. Since the fall of 2001, he has served on a congressionally appointed panel guiding technology at a division of the National Security Agency.

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Massive data streams, large quantities of data that arrive continuously, are becoming increasingly commonplace in many areas of science and technology. Consequently development of analytical methods for such streams is of growing importance. To address this issue, the National Security Agency asked the NRC to hold a workshop to explore methods for analysis of streams of data so as to stimulate progress in the field. This report presents the results of that workshop. It provides presentations that focused on five different research areas where massive data streams are present: atmospheric and meteorological data; high-energy physics; integrated data systems; network traffic; and mining commercial data streams. The goals of the report are to improve communication among researchers in the field and to increase relevant statistical science activity.

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