ML Anthology

Closest Pairs Data Selection for Support Vector Machines

Chaofan Sun
AAAI 2006 pp. 1926-1927
doi:10.1056/nejm199009133231112 /aaai/2006/sun2006aaai-closest/

Abstract

This paper presents data selection procedures for support vec-tor machines (SVM). The purpose of data selection is to re-duce the dataset by eliminating as many non support vectors (non-SVs) as possible. Based on the fact that support vec-tors (SVs) are those vectors close to the decision boundary, data selection keeps only the closest pair vectors of opposite classes. The selected dataset will replace the full dataset as the training component for any standard SVM algorithm.

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Text

Sun. "Closest Pairs Data Selection for Support Vector Machines." AAAI Conference on Artificial Intelligence, 2006. doi:10.1056/nejm199009133231112

Markdown

[Sun. "Closest Pairs Data Selection for Support Vector Machines." AAAI Conference on Artificial Intelligence, 2006.](https://mlanthology.org/aaai/2006/sun2006aaai-closest/) doi:10.1056/nejm199009133231112

BibTeX

@inproceedings{sun2006aaai-closest,
  title     = {{Closest Pairs Data Selection for Support Vector Machines}},
  author    = {Sun, Chaofan},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2006},
  pages     = {1926-1927},
  doi       = {10.1056/nejm199009133231112},
  url       = {https://mlanthology.org/aaai/2006/sun2006aaai-closest/}
}