Abstract
A new method of feature weighting, useful also for feature extraction has been described. It is quite efficient and gives quite accurate results. Weighting algorithm may be used with any kind of learning algorithm. The weighting algorithm with k-nearest neighbors model was used to estimate the best feature base for a given distance measure. Results obtained with this algorithm clearly show its superior performance in several benchmark tests.
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© 2003 Springer-Verlag Berlin Heidelberg
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Jankowski, N. (2003). Discrete Quasi-gradient Features Weighting Algorithm. In: Rutkowski, L., Kacprzyk, J. (eds) Neural Networks and Soft Computing. Advances in Soft Computing, vol 19. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1902-1_26
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DOI: https://doi.org/10.1007/978-3-7908-1902-1_26
Publisher Name: Physica, Heidelberg
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