Error back-propagation algorithm for classification of imbalanced data

Classification of imbalanced data is pervasive but it is a difficult problem to solve. In order to improve the classification of imbalanced data, this letter proposes a new error function for the error back-propagation algorithm of multilayer perceptrons. The error function intensifies weight-updati...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Neurocomputing (Amsterdam) Ročník 74; číslo 6; s. 1058 - 1061
Hlavní autor:	Oh, Sang-Hoon
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 15.02.2011
Témata:	Error back-propagation Error function Imbalanced data Imbalanced data Error back-propagation Error function
ISSN:	0925-2312, 1872-8286
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	Classification of imbalanced data is pervasive but it is a difficult problem to solve. In order to improve the classification of imbalanced data, this letter proposes a new error function for the error back-propagation algorithm of multilayer perceptrons. The error function intensifies weight-updating for the minority class and weakens weight-updating for the majority class. We verify the effectiveness of the proposed method through simulations on mammography and thyroid data sets.
ISSN:	0925-2312 1872-8286
DOI:	10.1016/j.neucom.2010.11.024