%B ESANN 2018 - Proceedings 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine LearningESANN 2017 - Proceedings 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
%I i6doc.com
%P 207-212
%C Bruges, Belgium
%L discovery10115865
%J ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
%A D Twomey
%A D Gorse
%X We introduce a new cost function for the training of a neural network classifier in conditions of high class imbalance. This function, based on an approximate confusion matrix, represents a balance of sensitivity and specificity and is thus well suited to problems where cost functions such as the mean squared error and cross entropy are prone to overpredicting the majority class. The benefit of the new measure is shown on a set of common class-imbalanced datasets using the Matthews Correlation Coefficient as an independent scoring measure.
%T A neural network cost function for highly class-imbalanced data sets
%O This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
%D 2018