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

Duarte Silva AP & Stam A (1996). Nonparametric Two-Group Classification: Concepts and a SAS-Based Software Package. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-96-127

[img]
Preview
Text
WP-96-127.pdf

Download (1MB) | Preview

Abstract

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.

Item Type: Monograph (IIASA Working Paper)
Research Programs: Institute Scholars (INS)
Depositing User: IIASA Import
Date Deposited: 15 Jan 2016 02:07
Last Modified: 13 Aug 2016 01:49
URI: http://pure.iiasa.ac.at/4900

Actions (login required)

View Item View Item

International Institute for Applied Systems Analysis (IIASA)
Schlossplatz 1, A-2361 Laxenburg, Austria
Phone: (+43 2236) 807 0 Fax:(+43 2236) 71 313