{"type":"ScholarlyArticle","title":"Semi-Supervised Learning with Explicit Misclassification Modeling","authors":[{"name":"Massih-Reza Amini","slug":"massih-reza-amini","given":"Massih-Reza","family":"Amini","affiliation":""},{"name":"Patrick Gallinari","slug":"patrick-gallinari","given":"Patrick","family":"Gallinari","affiliation":""}],"abstract":"This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This algorithm optimizes the classification maximum likelihood of a set of labeledunlabeled data, using a variant form of the Classification Expectation Maximization (CEM) algorithm. Its originality is that it makes use of both unlabeled data and of a probabilistic misclassification model for these data. The parameters of the labelerror model are learned together with the classifier parameters. We demonstrate the effectiveness of the approach on four data-sets and show the advantages of this method over a previously developed semi-supervised algorithm which does not consider imperfections in the labeling process.","doi":null,"url":"https://ijcai.org/proceedings/2003/82","pdf":"https://ijcai.org/proceedings/2003/0082.pdf","markdown":"https://ijcai.org/proceedings/2003/82.md","bibtex":"https://ijcai.org/proceedings/2003/bibtex/82","volume":{"slug":"2003","title":"Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2003","url":"https://ijcai.org/proceedings/2003/","year":2003,"location":"Acapulco, Mexico","dates":"","editors":"Georg Gottlob","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":82,"pages":{"first":555,"last":559},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}