Abstract
In this paper, we focus on the problem of feature selection with confidence machines (CM). CM allows us to make predictions within predefined confidence levels, thus providing a controlled and calibrated classification environment. We present a new feature selection method, namely Strangeness Minimisation Feature Selection, designed for CM. We apply this feature selection method to the problem of microarray classification and demonstrate its effectiveness. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Bellotti, T., Luo, Z., & Gammerman, A. (2006). Strangeness minimisation feature selection with confidence machines. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4224 LNCS, pp. 978–985). Springer Verlag. https://doi.org/10.1007/11875581_117
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