Self-Adapted and Filtered Qualitative Maximum a Posterior Algorithm for Small Data Sets

Hui Cao, Xiaoguang Gao

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper studies Bayesian network parameter learning from small data sets. Among existing techniques for parameter estimation in Bayesian network, qualitative maximum a posterior (QMAP) is state-of-the-art for small data sets. However, the uncertainty of pseudo prior statistic counts and the interference information in the broad prior constraints given by domain experts limit its performance. To further improve the learning accuracy and to eliminate interference information from given constraints, a self-adapted and filtered QMAP (SFQMAP) algorithm is proposed in this paper. The algorithm improves the learning performance by exploiting proper quantities of pseudo prior statistic count and applying the filtration model in QMAP. Via experiments on a series of examples we demonstrate that our approach is significantly more accurate than existing techniques for parameter learning from small data sets.

源语言英语
主期刊名Proceedings - 20th International Conference on High Performance Computing and Communications, 16th International Conference on Smart City and 4th International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018
出版商Institute of Electrical and Electronics Engineers Inc.
1585-1591
页数7
ISBN(电子版)9781538666142
DOI
出版状态已出版 - 22 1月 2019
活动20th International Conference on High Performance Computing and Communications, 16th IEEE International Conference on Smart City and 4th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018 - Exeter, 英国
期限: 28 6月 201830 6月 2018

出版系列

姓名Proceedings - 20th International Conference on High Performance Computing and Communications, 16th International Conference on Smart City and 4th International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018

会议

会议20th International Conference on High Performance Computing and Communications, 16th IEEE International Conference on Smart City and 4th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2018
国家/地区英国
Exeter
时期28/06/1830/06/18

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