Maroco, JoãoSilva, Dina Lúcia Gomes daGuerreiro, ManuelaMendonça, Alexandre deSantana, Isabel2012-09-122012-09-122012In Actas do XVII Congresso Anual da Sociedade Portuguesa de Estatística (pp. 241-251). Lisboa: Sociedade Portuguesa de Estatísticahttp://hdl.handle.net/10400.12/1691In this paper, we report a comparison study of 7 non parametric classifiers (Multilayer perceptron Neural Networks, Radial Basis Function Neural Networks, SupportVectorMachines, CART, CHAID and QUEST Classification trees and Random Forests) as compared to Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression tested in a real data application of mild cognitive impaired elderly patients conversion to dementia. When classification results are compared both on overall accuracy, specificity and sensitivity, Linear Discriminant Analysis and Random Forests rank first among all the classifiers.engPrediction of dementia patients: A comparative approach using parametric vs. non parametric classifiersconference object