Predicting accurate probabilities with a ranking loss.

TitlePredicting accurate probabilities with a ranking loss.
Publication TypeJournal Article
Year of Publication2012
AuthorsMenon, AKrishna, Jiang, XJ, Vembu, S, Elkan, C, Ohno-Machado, L
JournalMach Learn Int Conf Mach Learn
Volume2012
Pagination703-710
Date Published2012
iDASH CategoryStatistics
Abstract<p>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.</p>
Alternate JournalMach Learn Int Conf Mach Learn
PubMed ID25285328
PubMed Central IDPMC4180410
Grant ListR01 LM009520 / LM / NLM NIH HHS / United States
U54 HL108460 / HL / NHLBI NIH HHS / United States