SMOTEFRIS-INFFC: Handling the challenge of borderline and noisy examples in imbalanced learning for software defect prediction-Reference-Cited by-同舟云学术

SMOTEFRIS-INFFC: Handling the challenge of borderline and noisy examples in imbalanced learning for software defect prediction

Published:2020-01-09 Issue:1 Volume:38 Page:917-933
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Bashir Kamal¹²,Li Tianrui¹,Yohannese Chubato Wondaferaw¹,Yahaya Mahama³

Affiliation:

1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China

2. Department of Information Technology, College of Computer Science and Information Technology, Karary University, Omdurman, Sudan

3. School of Transport and Logistics Engineering, Southwest Jiaotong University, Chengdu, China

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference36 articles.

1. IEEE standard glossary of software engineering terminology;Radatz;IEEE Std,1990

2. Benchmarking classification models for software defect prediction: A proposed framework and novel findings;Lessmann;IEEE Transactions on Software Engineering,2008

3. A systematic review of software fault prediction studies;Catal;Expert Systems with Applications,2009

4. SMOTE: synthetic minority over-sampling technique;Chawla;Journal of Artificial Intelligence Research,2002

5. Enhancing software defect prediction using supervised-learning based framework;Bashir;12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE),2017

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