A sequential minimal optimization algorithm for the all-distances support vector machine. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), volume 6419 LNCS, pages 484-491, 2010. doi abstract bibtex The All-Distances SVM is a single-objective light extension of the binary μ-SVM for multi-category classification that is competitive against multi-objective SVMs, such as One-against-the-Rest SVMs and One-against-One SVMs. Although the model takes into account considerably less constraints than previous formulations, it lacks of an efficient training algorithm, making its use with medium and large problems impracticable. In this paper, a Sequential Minimal Optimization-like algorithm is proposed to train the All-Distances SVM, making large problems abordable. Experimental results with public benchmark data are presented to show the performance of the AD-SVM trained with this algorithm against other single-objective multi-category SVMs. © 2010 Springer-Verlag.
@inproceedings{10.1007/978-3-642-16687-7_64,
abstract = "The All-Distances SVM is a single-objective light extension of the binary μ-SVM for multi-category classification that is competitive against multi-objective SVMs, such as One-against-the-Rest SVMs and One-against-One SVMs. Although the model takes into account considerably less constraints than previous formulations, it lacks of an efficient training algorithm, making its use with medium and large problems impracticable. In this paper, a Sequential Minimal Optimization-like algorithm is proposed to train the All-Distances SVM, making large problems abordable. Experimental results with public benchmark data are presented to show the performance of the AD-SVM trained with this algorithm against other single-objective multi-category SVMs. © 2010 Springer-Verlag.",
year = "2010",
title = "A sequential minimal optimization algorithm for the all-distances support vector machine",
volume = "6419 LNCS",
pages = "484-491",
doi = "10.1007/978-3-642-16687-7\_64",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)"
}
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