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A boosting algorithm for regression

  • Part I: Coding and Learning in Biology
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Artificial Neural Networks — ICANN'97 (ICANN 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1327))

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Abstract

A new boosting algorithm ADABOOST-Ra for regression problems is presented and upper bound on the error is obtained. Experimental results to compare ADABOOST-RΔ and other learning algorithms are given.

Supported by grants CT 9305230.ST 74, CT 90.021.56.74

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References

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Authors and Affiliations

  1. Dipartimento di Scienze dell'Informazione, Università degli Studi di Milano, via Comelico 39/40, I-20135, Milano, Italy

    A. Bertoni, P. Campadelli & M. Parodi

Authors
  1. A. Bertoni
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  2. P. Campadelli
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  3. M. Parodi
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Editor information

Wulfram Gerstner Alain Germond Martin Hasler Jean-Daniel Nicoud

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© 1997 Springer-Verlag Berlin Heidelberg

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Bertoni, A., Campadelli, P., Parodi, M. (1997). A boosting algorithm for regression. In: Gerstner, W., Germond, A., Hasler, M., Nicoud, JD. (eds) Artificial Neural Networks — ICANN'97. ICANN 1997. Lecture Notes in Computer Science, vol 1327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0020178

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  • DOI: https://doi.org/10.1007/BFb0020178

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63631-1

  • Online ISBN: 978-3-540-69620-9

  • eBook Packages: Springer Book Archive

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