PASS: a simple classifier system for data analysis

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Show simple item record Muruzábal, Jorge
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística 2009-02-20T12:11:51Z 2009-02-20T12:11:51Z 1993-09
dc.description.abstract Let x be a vector of predictors and y a scalar response associated with it. Consider the regression problem of inferring the relantionship between predictors and response on the basis of a sample of observed pairs (x,y). This is a familiar problem for which a variety of methods are available. This paper describes a new method based on the classifier system approach to problem solving. Classifier systems provide a rich framework for learning and induction, and they have been suc:cessfully applied in the artificial intelligence literature for some time. The present method emiches the simplest classifier system architecture with some new heuristic and explores its potential in a purely inferential context. A prototype called PASS (Predictive Adaptative Sequential System) has been built to test these ideas empirically. Preliminary Monte Carlo experiments indicate that PASS is able to discover the structure imposed on the data in a wide array of cases.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working Papers. Statistics and Econometrics
dc.relation.ispartofseries 1993-20-16
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.subject.other Regression analysis
dc.subject.other Classifier systems
dc.subject.other Machine learning
dc.title PASS: a simple classifier system for data analysis
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
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