Anzeige
Erschienen in:
2007 | OriginalPaper | Buchkapitel
Feature Selection Based on Sensitivity Analysis
verfasst von : Noelia Sánchez-Maroño, Amparo Alonso-Betanzos
Erschienen in: Current Topics in Artificial Intelligence
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper an incremental version of the ANOVA and Functional Networks Feature Selection (AFN-FS) method is presented. This new wrapper method (IAFN-FS) is based on an incremental functional decomposition, thus eliminating the main drawback of the basic method: the exponential complexity of the functional decomposition. This complexity limited its scope of applicability, being only applicable to datasets with a relatively small number of features. The performance of the incremental version of the method was tested against several real data sets. The results show that IAFN-FS outperforms the accuracy obtained by other standard and novel feature selection methods, using a small set of features.