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An Evaluation of Support Vector Machines as a Pattern Recognition Tool

Machine Learning 2014-12-16 v1

Abstract

The purpose of this report is in examining the generalization performance of Support Vector Machines (SVM) as a tool for pattern recognition and object classification. The work is motivated by the growing popularity of the method that is claimed to guarantee a good generalization performance for the task in hand. The method is implemented in MATLAB. SVMs based on various kernels are tested for classifying data from various domains.

Keywords

Cite

@article{arxiv.1412.4186,
  title  = {An Evaluation of Support Vector Machines as a Pattern Recognition Tool},
  author = {Eugene Borovikov},
  journal= {arXiv preprint arXiv:1412.4186},
  year   = {2014}
}

Comments

A short (6 page) report on evaluation of the SVM as a pattern classification tool, as of 1999

R2 v1 2026-06-22T07:29:57.030Z