sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification

1 code implementation • 24 Aug 2021 • Gabriel Bénédict, Vincent Koops, Daan Odijk, Maarten de Rijke

We propose a loss function, sigmoidF1, which is an approximation of the F1 score that (1) is smooth and tractable for stochastic gradient descent, (2) naturally approximates a multilabel metric, and (3) estimates label propensities and label counts.

Classification