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2003 | OriginalPaper | Chapter

Improving Symbolic Regression with Interval Arithmetic and Linear Scaling

Author : Maarten Keijzer

Published in: Genetic Programming

Publisher: Springer Berlin Heidelberg

Included in: Professional Book Archive

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The use of protected operators and squared error measures are standard approaches in symbolic regression. It will be shown that two relatively minor modifications of a symbolic regression system can result in greatly improved predictive performance and reliability of the induced expressions. To achieve this, interval arithmetic and linear scaling are used. An experimental section demonstrates the improvements on 15 symbolic regression problems.

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Metadata
Title
Improving Symbolic Regression with Interval Arithmetic and Linear Scaling
Author
Maarten Keijzer
Copyright Year
2003
Publisher
Springer Berlin Heidelberg
Book
Genetic Programming

Print ISBN: 978-3-540-00971-9

Electronic ISBN: 978-3-540-36599-0

Copyright Year: 2003

DOI
https://doi.org/10.1007/3-540-36599-0_7