Coin Classification Using a Novel Technique for Learning Characteristic Decision Trees by Controlling the Degree of Generalization

@inproceedings{Davidsson1996CoinCU,
  title={Coin Classification Using a Novel Technique for Learning Characteristic Decision Trees by Controlling the Degree of Generalization},
  author={Paul Davidsson},
  booktitle={IEA/AIE},
  year={1996}
}
A novel method for learning characteristic decision trees is applied to the problem of learning the decision mechanism of coin-sorting machines. Decision trees constructed by ID3-like algorithms are unable to detect instances of categories not present in the set of training examples. Instead of being rejected, such instances are assigned to one of the classes actually present in the training set. To solve this problem the algorithm must learn characteristic, rather than discriminative, category… CONTINUE READING
Highly Cited
This paper has 40 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 25 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 14 references

Lund University

  • P. Davidsson. Autonomous Agents, the Concept of Concepts. PhD thesis, Department of Computer Science
  • Sweden,
  • 1996
3 Excerpts

Algorithmic Learning

  • A. Hutchinson
  • Clarendon Press
  • 1994
1 Excerpt

Master’s thesis)

  • E. Mårtensson. Improved coin classification
  • LU–CS–EX: 94–2, Dept. of Computer Science, Lund…
  • 1994
1 Excerpt

In IJCAI-93

  • T. Van de Merckt. Decision trees in numerical attribu spaces
  • pages 1016–1021. Morgan Kaufmann,
  • 1993
1 Excerpt

Quinlan

  • J.R
  • C4.5: Programs for Machine Learning. Morgan…
  • 1993
1 Excerpt

Applied Multivariate Statistical Analysis

  • R. A. Johnson, D. W. Wichern
  • Prentice-Hall
  • 1992

Similar Papers

Loading similar papers…