Statistical tests using hinge/?-sensitive loss

Yükleniyor...
Küçük Resim

Tarih

2013

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Springer-Verlag

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Araştırma projeleri

Organizasyon Birimleri

Dergi sayısı

Özet

Statistical tests used in the literature to compare algorithms use the misclassification error which is based on the 0/1 loss and square loss for regression. Kernel-based, support vector machine classifiers (regressors) however are trained to minimize the hinge (?-sensitive) loss and hence they should not be assessed or compared in terms of the 0/1 (square loss) but with the loss measure they are trained to minimize. We discuss how the paired t test can use the hinge (?-sensitive) loss and show in our experiments that doing that, we can detect differences that the test on error cannot detect, indicating higher power in distinguishing between the behavior of kernel-based classifiers (regressors). Such tests can be generalized to compare L > 2 algorithms.

Açıklama

Anahtar Kelimeler

Algorithms, Decision trees, Information science, Kernel based classifiers, Misclassification error, Neural networks, Statistical tests, Support vector machine classifiers, Support vector machines, T-tests

Kaynak

Computer and Information Sciences III - 27th International Symposium on Computer and Information Sciences, ISCIS 2012

WoS Q Değeri

Scopus Q Değeri

N/A

Cilt

Sayı

Künye

Yıldız, O. T. & Alpaydın, A. İ. E. (2013). Statistical tests using hinge/ε-sensitive loss. Paper presented at the Computer and Information Sciences III - 27th International Symposium on Computer and Information Sciences, ISCIS 2012, 153-160. doi:10.1007/978-1-4471-4594-3-16