Corpus ID: 2354909

Discussion of the Paper \additive Logistic Regression: a Statistical View of Boosting" By

@inproceedings{Friedman2000DiscussionOT,
  title={Discussion of the Paper \additive Logistic Regression: a Statistical View of Boosting" By},
  author={J. Friedman and T. Hastie and R. Tibshirani and Y. Freund and R. Schapire},
  year={2000}
}
  • J. Friedman, T. Hastie, +2 authors R. Schapire
  • Published 2000
  • The main and important contribution of this paper is in establishing a connection between boosting, a newcomer to the statistics scene, and additive models. One of the main properties of boosting that has made it interesting to statisticians and others is its relative (but not complete) immunity to overrtting. As pointed out by the authors, the current paper does not address this issue. Leo Breiman 1] tried to explain this behaviour in terms of bias and variance. In our paper with Bartlett and… CONTINUE READING
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    References

    SHOWING 1-4 OF 4 REFERENCES
    Boosting the margin: A new explanation for the effectiveness of voting methods
    • 2,686
    • PDF
    The Alternating Decision Tree Learning Algorithm
    • 756
    • PDF
    An Adaptive Version of the Boost by Majority Algorithm
    • 153
    Arcing classi ers
    • The Annals of Statistics,
    • 1998