Abstract
We propose a new feature selection criterion not based on calculated measures between attributes, or complex and costly distance calculations. Applying a wrapper to the output of a new attribute ranking method, we obtain a minimum subset with the same error rate as the original data. The experiments were compared to two other algorithms with the same results, but with a very short computation time.
This work has been supported by the Spanish Research Agency CICYT under grant TIC2001-1143-C03-02.
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Ruiz, R., Aguilar-Ruiz, J.S., Riquelme, J.C. (2004). Wrapper for Ranking Feature Selection. In: Yang, Z.R., Yin, H., Everson, R.M. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2004. IDEAL 2004. Lecture Notes in Computer Science, vol 3177. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28651-6_56
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DOI: https://doi.org/10.1007/978-3-540-28651-6_56
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