Gå til hovedinnhold
Publisert 2004

Read in English

Publikasjonsdetaljer

Tidsskrift : Computational Statistics & Data Analysis , vol. 46 , p. 689–705 , 2004

Utgiver : Elsevier

Internasjonale standardnummer :
Trykt : 0167-9473
Elektronisk : 1872-7352

Publikasjonstype : Vitenskapelig artikkel

Bidragsytere : Mevik, Bjørn-Helge

Har du spørsmål om noe vedrørende publikasjonen, kan du kontakte Nofimas bibliotekleder.

Kjetil Aune
Bibliotekleder
kjetil.aune@nofima.no

Sammendrag

The situation where classes arise by dividing the range of a continuous response variable into intervals is discussed. The focus is on assessing the performance of classifiers. Due to the underlying continuum, all misclassifications are not equally grave. The probability of misclassification (pmc) is not optimal in this situation. An alternative performance measure, the squared error rate (sqerr) is proposed. It is related to the mean squared error of regression, and penalises misclassifications according to their severity. Also, because of measurement errors in the response variable, there are misallocated class labels in data sets used for training and testing. Estimates of the pmc and the sqerr are developed for this situation. The estimates are tested and compared on a real data set and in a simulation.