A Case Study for Learning from Imbalanced Data Sets

Author:

An Aijun,Cercone Nick,Huang Xiangji

Publisher

Springer Berlin Heidelberg

Reference13 articles.

1. Aha, D. and Kibler, D. 1987. “Learning Representative Exemplars of Concepts: An Initial Case Study.” Proceedings of the Fourth International Conference on Machine Learning, Irvine, CA.

2. An, A. and Cercone, N. 1998. “ELEM2: A Learning System for More Accurate Classifications.” Proceedings of the 12th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, AI’98 (Lecture Notes in Artificial Intelligence 1418), Vancouver, Canada.

3. An, A. and Cercone, N. 2000. “Rule Quality Measures Improve the Accuracy of Rule Induction: An Experimental Approach.”, Proceedings of the 12th International Symposium on Methodologies for Intelligent Systems, Charlotte, NC. pp.119–129.

4. Bruha, I. 1996. “Quality of Decision Rules: Definitions and Classification Schemes for Multiple Rules.”, in Nakhaeizadeh, G. and Taylor, C. C. (eds.): Machine Learning and Statistics, The Interface. Jone Wiley & Sons Inc.

5. Cardie, C and Howe, N. 1997. “Improving Minority Class Prediction Using Case-Specific Feature Weights.”, Proceedings of the Fourteenth International Confernece on Machine Learning, Morgan Kaufmann. pp.57–65.

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Synthetic minority oversampling for function approximation problems;International Journal of Intelligent Systems;2019-09-09

2. An Ensemble Method Based on SVC and Euclidean Distance for Classification Binary Imbalanced Data;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2017-12-22

3. Adaptive Ensemble Method Based on Spatial Characteristics for Classifying Imbalanced Data;Scientific Programming;2017

4. BRACID: a comprehensive approach to learning rules from imbalanced data;Journal of Intelligent Information Systems;2011-12-30

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3