%0 Journal Article
%T Predicting accurate probabilities with a ranking loss
%A Aditya Menon
%A Xiaoqian Jiang
%A Shankar Vembu
%A Charles Elkan
%A Lucila Ohno-Machado
%J Computer Science
%D 2012
%I arXiv
%X In many real-world applications of machine learning classifiers, it is essential to predict the probability of an example belonging to a particular class. This paper proposes a simple technique for predicting probabilities based on optimizing a ranking loss, followed by isotonic regression. This semi-parametric technique offers both good ranking and regression performance, and models a richer set of probability distributions than statistical workhorses such as logistic regression. We provide experimental results that show the effectiveness of this technique on real-world applications of probability prediction.
%U http://arxiv.org/abs/1206.4661v1