{"type":"ScholarlyArticle","title":"Polytree-Augmented Classifier Chains for Multi-Label Classification","authors":[{"name":"Lu Sun","slug":"lu-sun","given":"Lu","family":"Sun","affiliation":""},{"name":"Mineichi Kudo","slug":"mineichi-kudo","given":"Mineichi","family":"Kudo","affiliation":""}],"abstract":"Multi-label classification is a challenging and appealing supervised learning problem where a subset of labels, rather than a single label seen in traditional classification problems, is assigned to a single test instance. Classifier chains based methods are a promising strategy to tackle multi-label classification problems as they model label correlations at acceptable complexity. However, these methods are difficult to approximate the underlying dependency in the label space, and suffer from the problems of poorly ordered chain and error propagation. In this paper, we propose a novel polytree-augmented classifier chains method to remedy these problems. A polytree is used to model reasonable conditional dependence between labels over attributes, under which the directional relationship between labels within causal basins could be appropriately determined. In addition, based on the max-sum algorithm, exact inference would be performed on polytrees at reasonable cost, preventing from error propagation. The experiments performed on both artificial and benchmark multi-label data sets demonstrated that the proposed method is competitive with the state-of-the-art multi-label classification methods.","doi":null,"url":"https://ijcai.org/proceedings/2015/539","pdf":"https://ijcai.org/proceedings/2015/0539.pdf","markdown":"https://ijcai.org/proceedings/2015/539.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/539","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Special Track on Machine Learning","track":"Special Track on Machine Learning","number":539,"pages":{"first":3834,"last":3839},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}