Nonparametric Two-Group Classification: Concepts and a SAS-Based Software Package

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WP-96-127.pdf

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WP-96-127.pdf

http://eprints.org/relation/isVersionOf https://pure.iiasa.ac.at/id/document/4198 http://eprints.org/relation/isVolatileVersionOf https://pure.iiasa.ac.at/id/document/4198 http://eprints.org/relation/isCoversheetVersionOf https://pure.iiasa.ac.at/id/document/4198 archive 351 disk0/00/00/49/00 2016-01-15 02:07:37 2021-08-27 17:15:39 2016-01-15 02:07:37 monograph show 2 Duarte Silva A.P. Stam A. 1602 Nonparametric Two-Group Classification: Concepts and a SAS-Based Software Package pub iis_cmp iis_met prog_ins In this paper, we introduce BestClass, a set of SAS macros, available in the mainframe and workstation environment, designed for solving two-group classification problems using a class of recently developed nonparametric classification methods. The criteria used to estimate the classification function are based on either minimizing a function of the absolute deviations from the surface which separates the groups, or directly minimizing a function of the number of misclassified entities in the training sample. The solution techniques used by BestClass to estimate the classification rule utilize the mathematical programming routines of the SAS/OR@ software. Recently, a number of research studies have reported that under certain data conditions this class of classification methods can provide more accurate classification results than existing methods, such as Fisher's linear discriminant function and logistic regression. However, these robust classification methods have not yet been implemented in the major statistical packages, and hence are beyond the reach of those statistical analysts who are unfamiliar with mathematical programming techniques. We use a limited simulation experiment and an example to compare and contrast properties of the methods included in BestClass with existing parametric and nonparametric methods. We believe that BestClass contributes significantly to the field of nonparametric classification analysis, in that it provides the statistical community with convenient access to this recently developed class of methods. BestClass is available from the authors. 1996-12 published WP-96-127 WP-96-127 10 1588 public working_paper IIASA, Laxenburg, Austria 43 FALSE info:eu-repo/semantics/book