Abstract
This paper presents an efficient approach for supporting decremental learning for incremental proximal support vector machines (SVM). The presented decremental algorithm based on decay coefficients is compared with an existing window-based decremental algorithm, and is shown to perform at a similar level in accuracy, but providing significantly better computational performance.
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Tveit, A., Hetland, M.L., Engum, H. (2003). Incremental and Decremental Proximal Support Vector Classification using Decay Coefficients. In: Kambayashi, Y., Mohania, M., Wöß, W. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2003. Lecture Notes in Computer Science, vol 2737. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45228-7_42
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DOI: https://doi.org/10.1007/978-3-540-45228-7_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40807-9
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