Fast Sparse Approximation for Least Squares Support Vector Machine

@article{Jiao2007FastSA,
  title={Fast Sparse Approximation for Least Squares Support Vector Machine},
  author={Licheng Jiao and Liefeng Bo and Ling Wang},
  journal={IEEE Transactions on Neural Networks},
  year={2007},
  volume={18},
  pages={685-697}
}
In this paper, we present two fast sparse approximation schemes for least squares support vector machine (LS-SVM), named FSALS-SVM and PFSALS-SVM, to overcome the limitation of LS-SVM that it is not applicable to large data sets and to improve test speed. FSALS-SVM iteratively builds the decision function by adding one basis function from a kernel-based dictionary at one time. The process is terminated by using a flexible and stable epsilon insensitive stopping criterion. A probabilistic… CONTINUE READING
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