A hybrid machine learning framework for analyzing human decision-making through learning preferences * , **
Guo, Mengzhuo1,2; Zhang, Qingpeng2; Liao, Xiuwu1; Chen, Frank Youhua3; Zeng, Daniel Dajun4
发表期刊OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
ISSN0305-0483
2021-06-01
卷号101页码:18
通讯作者Zhang, Qingpeng(qingpeng.zhang@cityu.edu.hk)
摘要Multiple criteria decision aiding (MCDA) is a family of analytic approaches to depicting the rationale of human decisions. To better interpret the contributions of individual attributes to the decision maker, the conventional MCDA approaches assume that the attributes are monotonic and preference independence. However, the capacity in describing the decision maker & rsquo;s preferences is sacrificed as a result of model simplification. To meet the decision maker & rsquo;s demand for more accurate and interpretable decision models, we propose a novel hybrid method, namely Neural Network-based Multiple Criteria Decision Aiding (NN-MCDA), which combines MCDA model and machine learning to achieve better prediction performance while capturing the relationships between individual attributes and the prediction. NN-MCDA uses a linear component (in an additive form of a set of polynomial functions) to characterize such relationships through providing explicit non-monotonic marginal value functions, and a nonlinear component (in a standard multilayer perceptron form) to capture the implicit high-order interactions among attributes and their complex nonlinear transformations. We demonstrate the effectiveness of NN-MCDA with extensive simulation studies and three real-world datasets. The study sheds light on how to improve the prediction performance of MCDA models using machine learning techniques, and how to enhance the interpretability of machine learning models using MCDA approaches. (c) 2020 Elsevier Ltd. All rights reserved.
关键词Decision analysis Business analytics Predictive modeling Big data analytics Machine learning Multiple criteria decision analysis
DOI10.1016/j.omega.2020.102263
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[71972164] ; National Natural Science Foundation of China[71672163] ; National Natural Science Foundation of China[71872144] ; National Natural Science Foundation of China[91846110] ; National Natural Science Foundation of China[71621002] ; Health and Medical Research Fund[16171991] ; Chinese Academy of Sciences[ZDRW-XH-2017-3] ; Ministry of Science and Technology of the People's Republic of China[2016QY02D0305]
项目资助者National Natural Science Foundation of China ; Health and Medical Research Fund ; Chinese Academy of Sciences ; Ministry of Science and Technology of the People's Republic of China
WOS研究方向Business & Economics ; Operations Research & Management Science
WOS类目Management ; Operations Research & Management Science
WOS记录号WOS:000626604000010
出版者PERGAMON-ELSEVIER SCIENCE LTD
引用统计
被引频次:26[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/44046
专题多模态人工智能系统全国重点实验室_互联网大数据与信息安全
通讯作者Zhang, Qingpeng
作者单位1.Xi An Jiao Tong Univ, Sch Management, Key Lab Minist Educ Proc Control & Efficiency Eng, Xian 710049, Peoples R China
2.City Univ Hong Kong, Sch Data Sci, Hong Kong 999077, Peoples R China
3.City Univ Hong Kong, Coll Business, Dept Management Sci, Hong Kong 999077, Peoples R China
4.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100049, Peoples R China
推荐引用方式
GB/T 7714
Guo, Mengzhuo,Zhang, Qingpeng,Liao, Xiuwu,et al. A hybrid machine learning framework for analyzing human decision-making through learning preferences * , **[J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE,2021,101:18.
APA Guo, Mengzhuo,Zhang, Qingpeng,Liao, Xiuwu,Chen, Frank Youhua,&Zeng, Daniel Dajun.(2021).A hybrid machine learning framework for analyzing human decision-making through learning preferences * , **.OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE,101,18.
MLA Guo, Mengzhuo,et al."A hybrid machine learning framework for analyzing human decision-making through learning preferences * , **".OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE 101(2021):18.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Guo, Mengzhuo]的文章
[Zhang, Qingpeng]的文章
[Liao, Xiuwu]的文章
百度学术
百度学术中相似的文章
[Guo, Mengzhuo]的文章
[Zhang, Qingpeng]的文章
[Liao, Xiuwu]的文章
必应学术
必应学术中相似的文章
[Guo, Mengzhuo]的文章
[Zhang, Qingpeng]的文章
[Liao, Xiuwu]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。