1999 LargeMarginClassUsingThePerceptAlg

From GM-RKB
Jump to navigation Jump to search

Subject Headings: Voted Perceptron Algorithm, Linear Classifier.

Notes

Cited By

Quotes

Abstract

  • We introduce and analyze a new algorithm for linear classification which combines Rosenblatt's perceptron algorithm with Helmbold and Warmuth's leave-one-out method. Like Vapnik's maximal-margin classifier, our algorithm takes advantage of data that are linearly separable with large margins. Compared to Vapnik's algorithm, however, ours is much simpler to implement, and much more efficient in terms of computation time. We also show that our algorithm can be efficiently used in very high dimensional spaces using kernel functions. We performed some experiments using our algorithm, and some variants of it, for classifying images of handwritten digits. The performance of our algorithm is close to, but not as good as, the performance of maximal-margin classifiers on the same problem, while saving significantly on computation time and programming effort.

References

BibTeX

@article{1999_LargeMarginClassUsingThePerceptAlg,
  author    = {Yoav Freund and
               Robert E. Schapire},
  title     = {Large Margin Classification Using the Perceptron Algorithm},
  journal   = {Machine Learning},
  volume    = {37},
  number    = {3},
  pages     = {277--296},
  year      = {1999},
  url       = {https://doi.org/10.1023/A:1007662407062},
  doi       = {10.1023/A:1007662407062},
}


 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
1999 LargeMarginClassUsingThePerceptAlgYoav Freund
Robert E. Schapire
Large Margin Classification Using the Perceptron AlgorithmMachine Learning (ML) Subject Areahttp://www.cse.ucsd.edu/~yfreund/papers/LargeMarginsUsingPerceptron.ps10.1023/A:10076624070621999