MIDL 2021, K2, Bridge et. al., Short Oral
Channel: MIDL Society
Date: 2021-08-06

K2 - mGEV: Extension of the GEV Activation to Multiclass Classification

Joshua Thomas Bridge, Yalin Zheng

Conference page: https://2021.midl.io/papers/K2

Abstract: Unbalanced data is a significant problem when training machine learning algorithms; the algorithm often overfits on the dominant class and neglects the smaller classes. The generalized extreme value (GEV) distribution has recently been proposed to mitigate this overfitting on binary classification problems. We extend this to multiclass problems and show that the multiclass GEV similarly reduces overfitting. Experiments are conducted on two datasets showing improved performance over the commonly used softmax activation. Code for the mGEV activation is available at https://github.com/JTBridge/GEV.