A parallel SVM training algorithm on large-scale classification problems

@article{Zhang2005APS,
  title={A parallel SVM training algorithm on large-scale classification problems},
  author={Jian-pei Zhang and Zhong-Wei Li and Jing Yang},
  journal={2005 International Conference on Machine Learning and Cybernetics},
  year={2005},
  volume={3},
  pages={1637-1641 Vol. 3}
}
Support vector machine (SVM) has become a popular classification tool but the main disadvantages of SVM algorithms are their large memory requirement and computation time to deal with very large datasets. To speed up the process of training SVM, parallel methods have been proposed by splitting the problem into smaller subsets and training a network to assign samples of different subsets. A parallel training algorithm on large-scale classification problems is proposed, in which multiple SVM… CONTINUE READING
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