SDL, a stochastic algorithm for learning decision lists with limited complexity

@article{Gomes1993SDLAS,
  title={SDL, a stochastic algorithm for learning decision lists with limited complexity},
  author={Fernando de Carvalho Gomes and Olivier Gascuel},
  journal={Annals of Mathematics and Artificial Intelligence},
  year={1993},
  volume={10},
  pages={281-302}
}
This paper deals with learning decision lists from examples. In real world problems, data are often noisy and imperfectly described. It is commonly acknowledged that in such cases, consistent but inevitably complex classification procedures usually cause overfitting: results are perfect on the learning set but worse on new examples. Therefore, one searches for less complex procedures which are almost consistent or, in other words, for a good compromise between complexity and goodness-of-fit… CONTINUE READING

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