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Where Should We Stop? An Investigation on Early Stopping for GP Learning

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Book cover Simulated Evolution and Learning (SEAL 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7673))

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Abstract

We investigate the impact of early stopping on the speed and accuracy of Genetic Programming (GP) learning from noisy data. Early stopping, using a popular stopping criterion, maintains the generalisation capacity of GP while significantly reducing its training time.

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Author information

Authors and Affiliations

  1. Le Quy Don University, Vietnam

    Thi Hien Nguyen & Quang Uy Nguyen

  2. Hanoi University, Vietnam

    Xuan Hoai Nguyen

  3. Seoul National University, Korea

    Bob McKay

Authors
  1. Thi Hien Nguyen
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  2. Xuan Hoai Nguyen
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  3. Bob McKay
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  4. Quang Uy Nguyen
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Editor information

Editors and Affiliations

  1. Faculty of Information Technology, Le Quy Don Technical University, 100 Hoang Quoc Viet Street, Cau Giay District,, Hanoi, Vietnam

    Lam Thu Bui

  2. School of Computer Engineering, Nanyang Technological University, Block N4, 2b-39, Nanyang Avenue, 639798,, Singapore, Singapore

    Yew Soon Ong

  3. Faculty of Information Technology,, Hanoi University, km9 Nguyen Trai Road, Hanoi, Vietnam

    Nguyen Xuan Hoai

  4. Graduate School of Engineering, Department of Computer Science, Osaka Prefecture University, 1-1 Gakuen-cho, Nakaku, 599-8531, Sakai, Osaka, Japan

    Hisao Ishibuchi

  5. School of Electrical and Electronic Engineering, Nanyang Technological University, Block N4, 2b-39, Nanyang Avenue, 639798, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

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© 2012 Springer-Verlag Berlin Heidelberg

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Nguyen, T.H., Nguyen, X.H., McKay, B., Nguyen, Q.U. (2012). Where Should We Stop? An Investigation on Early Stopping for GP Learning. In: Bui, L.T., Ong, Y.S., Hoai, N.X., Ishibuchi, H., Suganthan, P.N. (eds) Simulated Evolution and Learning. SEAL 2012. Lecture Notes in Computer Science, vol 7673. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34859-4_39

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  • DOI: https://doi.org/10.1007/978-3-642-34859-4_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34858-7

  • Online ISBN: 978-3-642-34859-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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