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Learning decision lists from noisy examples

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Book cover Mathematical Foundations of Computer Science 1993 (MFCS 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 711))

  • 208 Accesses

Abstract

In this paper we solve an open problem raised by Rivest.

This work was supported by National Sciences Foundation of China under Grant 6907330

On visit Institute for Informatics, Slovak Academy of Sciences, partially supported by Grant of Slovak Academy of Sciences No.88, by EC Cooperative Action IC 1000 Algorithms for Future Technologies

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References

  1. Angluin,D. Smith,C. (1983) Indutive inference: Theory and Methods ACM Comp. Surveys, 15(3),237–270.

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  2. Laird,P.D. (1988) Learning from Good and Bad Data. Kluwer Academic Publishers.

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  3. Rivest,R.L. (1987) Learning Decision Lists. Machine Learning,2:229–246.

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  4. Valiat,L.G. (1984) A theory of the learnable. Comm. ACM, 27,No.11, 1134–1142.

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Author information

Authors and Affiliations

  1. Computer Center, Fudan University, 200433, Shanghai, China

    Jilei Yin

  2. Computer Science Dept., Fudan University, 200433, Shanghai, China

    Zhu Hong

Authors
  1. Jilei Yin
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  2. Zhu Hong
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Editor information

Andrzej M. Borzyszkowski Stefan Sokołowski

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© 1993 Springer-Verlag Berlin Heidelberg

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Yin, J., Hong, Z. (1993). Learning decision lists from noisy examples. In: Borzyszkowski, A.M., Sokołowski, S. (eds) Mathematical Foundations of Computer Science 1993. MFCS 1993. Lecture Notes in Computer Science, vol 711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57182-5_67

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  • DOI: https://doi.org/10.1007/3-540-57182-5_67

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57182-7

  • Online ISBN: 978-3-540-47927-7

  • eBook Packages: Springer Book Archive

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