{"type":"ScholarlyArticle","title":"A Probabilistic Approach to Latent Cluster Analysis","authors":[{"name":"Zhipeng Xie","slug":"zhipeng-xie","given":"Zhipeng","family":"Xie","affiliation":""},{"name":"Rui Dong","slug":"rui-dong","given":"Rui","family":"Dong","affiliation":""},{"name":"Zhengheng Deng","slug":"zhengheng-deng","given":"Zhengheng","family":"Deng","affiliation":""},{"name":"Zhenying He","slug":"zhenying-he","given":"Zhenying","family":"He","affiliation":""},{"name":"Weidong Yang","slug":"weidong-yang","given":"Weidong","family":"Yang","affiliation":""}],"abstract":"Facing a large number of clustering solutions, cluster ensemble method provides an effective approach to aggregating them into a better one. In this paper, we propose a novel cluster ensemble method from probabilistic perspective. It assumes that each clustering solution is generated from a latent cluster model, under the control of two probabilistic parameters. Thus, the cluster ensemble problem is reformulated into an optimization problem of maximum likelihood. An EM-style algorithm is designed to solve this problem. It can determine the number of clusters automatically. Experimental results have shown that the proposed algorithm outperforms the state-of-the-art methods including EAC-AL, CSPA, HGPA, and MCLA. Furthermore, it has been shown that our algorithm is stable in the predicted numbers of clusters.","doi":null,"url":"https://ijcai.org/proceedings/2013/268","pdf":"https://ijcai.org/proceedings/2013/0268.pdf","markdown":"https://ijcai.org/proceedings/2013/268.md","bibtex":"https://ijcai.org/proceedings/2013/bibtex/268","volume":{"slug":"2013","title":"Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2013","url":"https://ijcai.org/proceedings/2013/","year":2013,"location":"Beijing, China","dates":"3–9 August 2013","editors":"Francesca Rossi","isbn":"978-1-57735-633-2","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":268,"pages":{"first":1813,"last":1818},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}