Large Scale Classification with Support Vector Machine Algorithms

@article{Do2007LargeSC,
  title={Large Scale Classification with Support Vector Machine Algorithms},
  author={Thanh-Nghi Do and Jean-Daniel Fekete},
  journal={Sixth International Conference on Machine Learning and Applications (ICMLA 2007)},
  year={2007},
  pages={7-12}
}
Boosting of least-squares support vector machine (LS-SVM) algorithms can classify large datasets on standard personal computers (PCs). We extend the LS-SVM proposed by Suykens and Vandewalle in several ways to efficiently classify large datasets. We developed a row-incremental version for datasets with billions of data points and up to 10,000 dimensions. By adding a Tikhonov regularization term and using the Sherman-Morrison-Woodbury formula, we developed a column-incremental LS-SVM to process… CONTINUE READING
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