title: An active learning approach with uncertainty, representativeness, and diversity.
abstract: Big data from the Internet of Things may create big challenge for data classification. Most active learning approaches select either uncertain or representative unlabeled instances to query their labels. Although several active learning algorithms have been proposed to combine the two criteria for query selection, they are usually ad hoc in finding unlabeled instances that are both informative and representative and fail to take the diversity of instances into account. We address this challenge by presenting a new active learning framework which considers uncertainty, representativeness, and diversity creation. The proposed approach provides a systematic way for measuring and combining the uncertainty, representativeness, and diversity of an instance. Firstly, use instances' uncertainty and representativeness to constitute the most informative set. Then, use the kernel k-means clustering algorithm to filter the redundant samples and the resulting samples are queried for labels. Extensive experimental results show that the proposed approach outperforms several state-of-the-art active learning approaches.
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
authors.forename: Tianxu
authors.initials: T
authors.lastname: He
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China ; State Key Lab. for Novel Software Technology, Nanjing University, Nanjing 210093, China.
authors.forename: Shukui
authors.initials: S
authors.lastname: Zhang
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China ; State Key Lab. for Novel Software Technology, Nanjing University, Nanjing 210093, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Xin
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
authors.forename: Pengpeng
authors.identifier: 0000-0002-3099-4523
authors.initials: P
authors.lastname: Zhao
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
authors.forename: Jian
authors.identifier: 0000-0002-8759-7107
authors.initials: J
authors.lastname: Wu
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China ; Suzhou Vocational University, Suzhou 215104, China.
authors.forename: Xuefeng
authors.initials: X
authors.lastname: Xian
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
authors.forename: Chunhua
authors.initials: C
authors.lastname: Li
authors.affiliation: School of Computer Science and Technology, Soochow University, Suzhou 215006, China ; Suzhou Vocational University, Suzhou 215104, China.
authors.forename: Zhiming
authors.initials: Z
authors.lastname: Cui
mesh_terms: D000465:Algorithms; D003199:Computer Systems