Selecting Models from Data
Artificial Intelligence and Statistics IV
Editors: Cheeseman, P., Oldford, R.W. (Eds.)
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- About this book
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This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.
- Table of contents (49 chapters)
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Statistical strategy: step 1
Pages 3-9
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Rational Learning: Finding a Balance Between Utility and Efficiency
Pages 11-20
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A new criterion for selecting models from partially observed data
Pages 21-29
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Small-sample and large-sample statistical model selection criteria
Pages 31-39
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On the choice of penalty term in generalized FPE criterion
Pages 41-49
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Table of contents (49 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Selecting Models from Data
- Book Subtitle
- Artificial Intelligence and Statistics IV
- Editors
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- P. Cheeseman
- R.W. Oldford
- Series Title
- Lecture Notes in Statistics
- Series Volume
- 89
- Copyright
- 1994
- Publisher
- Springer-Verlag New York
- Copyright Holder
- Springer-Verlag New York, Inc.
- eBook ISBN
- 978-1-4612-2660-4
- DOI
- 10.1007/978-1-4612-2660-4
- Softcover ISBN
- 978-0-387-94281-0
- Series ISSN
- 0930-0325
- Edition Number
- 1
- Number of Pages
- X, 487
- Number of Illustrations
- 6 b/w illustrations
- Topics
