Papa, João Paulo [UNESP]Falcão, Alexandre Xavier2023-03-022023-03-022022-01-24Optimum-Path Forest: Theory, Algorithms, and Applications, p. 217-219.http://hdl.handle.net/11449/242086In the past years, we have observed an increasing number of applications that require machine learning techniques to sort out problems that are not straightforward to humans. The reasons vary from information that is not clearly visible to the human eye (e.g., microscopic patterns in medical images) or the massive amount of data to analyze. This book aimed to shed light on the Optimum-Path Forest framework, which comprises approaches to dealing with supervised, semi-supervised, and unsupervised learning. Different applications have been presented together with a theoretical background concerning the techniques presented here. We expect to call the attention and curiosity of the readers towards OPF-based techniques and their strengths. © 2022 Copyright217-219engClusteringDeep learningMachine learningOptimum-path forestSupervised learningCapítulo de livro10.1016/B978-0-12-822688-9.00017-72-s2.0-85134954561