Kristen Jaskie, Andreas Spanias

Research output: Chapter in Book/Report/Conference proceedingChapter


Just as supervised classification is used in many fields and for a variety of purposes, PU learning is extremely versatile and can be used in almost every application area of ML that involves classification. PU learning is used for automatic label identification in poorly supervised learning problems. In some areas, such as the biomedical field, PU learning is a natural fit as obtaining negative samples can be difficult or even impossible in some cases. In this chapter we present a survey of some existing PU applications to both illustrate work that is being done in this field and to encourage new ideas and directions for further research. These applications have been broken into broad, occasionally overlapping, categories and will be presented in alphabetical order in the sections below.

Original languageEnglish (US)
Title of host publicationSynthesis Lectures on Artificial Intelligence and Machine Learning
PublisherSpringer Nature
Number of pages15
StatePublished - 2022

Publication series

NameSynthesis Lectures on Artificial Intelligence and Machine Learning
ISSN (Print)1939-4608
ISSN (Electronic)1939-4616

ASJC Scopus subject areas

  • Artificial Intelligence


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