Int. J. Computational Intelligence Studies, Vol. 1, No. 2, 2009 163 Copyright © 2009 Inderscience Enterprises Ltd. An experimental analysis of the impact of accuracy degradation in SVM classification D. Malchiodi Department of Computer Science, University of Milan, Via Comelico 39/41, 20135 Milano, Italy Fax: +39 0250316333 E-mail: malchiodi@dsi.unimi.it Abstract: The aim of this paper is to analyse the phenomenon of accuracy degradation in the samples given as input to SVM classification algorithms. In particular, the effect of accuracy degradation on the performance of the learnt classifiers is investigated and compared, if possible, with theoretical results. The study shows how a family of SVM classification algorithms enhanced in order to deal with quality measures on the available data handles accuracy degradation better than the classical SVM approaches to classification. Keywords: data quality; accuracy; data quality in classification; support vector classification; machine learning; accuracy degradation; computational intelligence. Reference to this paper should be made as follows: Malchiodi, D. (2009) ‘An experimental analysis of the impact of accuracy degradation in SVM classification’, Int. J. Computational Intelligence Studies, Vol. 1, No. 2, pp.163–190. Biographical notes: Dario Malchiodi received a degree in Computer Science in 1996 and a PhD in Applied Mathematics in 2000, both from the Milan University, Italy. He is an Assistant Professor at the same university, where he teaches laboratory of computer programming, advanced programming and simulation. His main research area range from probability theory and mathematical statistics to various aspect of computational and machine learning, with particular emphasis to the effect of data quality on machine learning problems. 1 Introduction The ISO 0402-1986 report defines quality as ‘the totality of feature and characteristics of a product or service that bear on its ability to satisfy stated or implied methods’ (ISO, 1994; Eurostat, 2003). Note how this definition poses equal emphasis on the terms product and service, where the difference between them refers to the physical/immaterial dimension, although the field of product manufacturing has faced quality issues since long time (see e.g., Burr, 1953), whereas similar instances gained importance only recently w.r.t. service management (Parasuraman et al., 1985). The definition also implicitly highlights the relation between quality and value of a product or service. Indeed, economists have focused since more than 30 years on quality issues (Garvin, 1983; Liepins, 1989; Porter and Millar, 1985; Te’eni, 1993) and on the additional costs