Abstract
In this paper a method for feature selection based on analysis of variance and using functional networks as induction algorithm is presented. It follows a backward selection search, but several features are discarded in the same step. The method proposed is compared with two SVM based methods, obtaining a smaller set of features with a similar accuracy.
This work has been partially funded by the Spanish Ministry of Science and Technology under project TIC-2003-00600 with FEDER funds.
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Sánchez-Maroño, N., Caamaño-Fernández, M., Castillo, E., Alonso-Betanzos, A. (2006). Functional Networks and Analysis of Variance for Feature Selection. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_123
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DOI: https://doi.org/10.1007/11875581_123
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