According to statistical learning theory, we propose a feature selection method using support vector machines (SVMs). By exploiting the power of SVMs, we integrate the two tasks, feature selection and classifier training, into a single consistent framework and make the feature selection process more effective. Our experiments show that our SVM feature selection method can speed up the classification process and improve the generalization performance of the classifier. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Fan, Z. G., Wang, K. A., & Lu, B. L. (2004). Feature selection for fast image classification with support vector machines. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3316, 1026–1031. https://doi.org/10.1007/978-3-540-30499-9_159
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