Prediction of dementia patients: A comparative approach using parametric vs. non parametric classifiers

Maroco, João; Silva, Dina Lúcia Gomes da; Guerreiro, Manuela; Mendonça, Alexandre de; Santana, Isabel

http://hdl.handle.net/10400.12/1691

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Authors

Maroco, João

Silva, Dina Lúcia Gomes da

Guerreiro, Manuela

Mendonça, Alexandre de

Santana, Isabel

Abstract(s)

In 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.