A novel random forest approach for imbalance problem in crime linkage

doi:10.1016/j.knosys.2020.105738

	A novel random forest approach for imbalance problem in crime linkage
	Li, Yu-Sheng; Chi, Hong; Shao, Xue-Yan; Qi, Ming-Liang; Xu, Bao-Guang
刊名	KNOWLEDGE-BASED SYSTEMS
	2020
卷号	195
DOI	10.1016/j.knosys.2020.105738
英文摘要	Crime linkage is a challenging task in crime analysis, which is to find serial crimes committed by the same offenders. It can be regarded as a binary classification task detecting serial case pairs. However, most case pairs in the real world are nonserial, so there is a serious class imbalance in the crime linkage. In this paper, we propose a novel random forest based on the information granule. The approach does not resample the minority class or the majority class but concentrates on indistinguishable case pairs at the classification boundary. The information granule is used to identify case pairs that are difficult to distinguish in the dataset and constructs a nearly balanced dataset in the uncertainty region to deal with the imbalanced problem. In the proposed approach, random trees come from the original dataset and the above mentioned nearly balanced dataset. A real-world robbery dataset and some public imbalanced datasets are employed to measure the performance of the approach. The results show that the proposed approach is effective in dealing with class imbalances, and it can be extended to combine with other methods solving class imbalances. (C) 2020 Elsevier B.V. All rights reserved.
语种	英语
内容类型	期刊论文
源URL	[http://ir.casisd.cn/handle/190111/9811]
专题	中国科学院科技战略咨询研究院
推荐引用方式 GB/T 7714	Li, Yu-Sheng,Chi, Hong,Shao, Xue-Yan,et al. A novel random forest approach for imbalance problem in crime linkage[J]. KNOWLEDGE-BASED SYSTEMS,2020,195.
APA	Li, Yu-Sheng,Chi, Hong,Shao, Xue-Yan,Qi, Ming-Liang,&Xu, Bao-Guang.(2020).A novel random forest approach for imbalance problem in crime linkage.KNOWLEDGE-BASED SYSTEMS,195.
MLA	Li, Yu-Sheng,et al."A novel random forest approach for imbalance problem in crime linkage".KNOWLEDGE-BASED SYSTEMS 195(2020).