Stoppiglia, Hervé; Dreyfus, Gérard; Dubois, Rémi; Oussar, Yacine Ranking a random feature for variable and feature selection. (English) Zbl 1102.68598 J. Mach. Learn. Res. 3, No. 7-8, 1399-1414 (2003). Summary: We describe a feature selection method that can be applied directly to models that are linear with respect to their parameters, and indirectly to others. It is independent of the target machine. It is closely related to classical statistical hypothesis tests, but it is more intuitive, hence more suitable for use by engineers who are not statistics experts. Furthermore, some assumptions of classical tests are relaxed. The method has been used successfully in a number of applications that are briefly described. Cited in 14 Documents MSC: 68T05 Learning and adaptive systems in artificial intelligence Keywords:Gram-Schmidt orthogonalization; statistical tests; information filtering PDFBibTeX XMLCite \textit{H. Stoppiglia} et al., J. Mach. Learn. Res. 3, No. 7--8, 1399--1414 (2003; Zbl 1102.68598) Full Text: DOI