Using bandit algorithms for selecting feature reduction techniques in software defect prediction-Reference-Cited by-同舟云学术

Using bandit algorithms for selecting feature reduction techniques in software defect prediction

Published:2022-05-23 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 19th International Conference on Mining Software Repositories
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Author:

Tsunoda Masateru¹,Monden Akito²,Toda Koji³,Tahir Amjed⁴,Bennin Kwabena Ebo⁵,Nakasai Keitaro⁶,Nagura Masataka⁷,Matsumoto Kenichi⁸

Affiliation:

1. Kindai University, Higashi-osaka, Japan

2. Okayama University, Okayama, Japan

3. Fukuoka Institute of Tech., Fukuoka, Japan

4. Massey University, Palmerston North, NZ

5. Wageningen UR, Wageningen, Netherlands

6. Kumamoto College, Kirishima, Japan

7. Nanzan University, Nagoya, Japan

8. NAIST, Ikoma, Japan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3524842.3529093

Reference36 articles.

1. Using Coupling-Based Weights for the Class Integration and Test Order Problem

2. A new look at the statistical model identification

3. Defect Prediction Using Akaike and Bayesian Information Criterion

4. T. Asano , M. Tsunoda , K. Toda , A. Tahir , K. Bennin , K. Nakasai , A. Monden , and K. Matsumoto , 2021. Using Bandit Algorithms for Project Selection in Cross-Project Defect Prediction . In Proc. of International Conference on Software Maintenance and Evolution (ICSME). 649--653 . T. Asano, M. Tsunoda, K. Toda, A. Tahir, K. Bennin, K. Nakasai, A. Monden, and K. Matsumoto, 2021. Using Bandit Algorithms for Project Selection in Cross-Project Defect Prediction. In Proc. of International Conference on Software Maintenance and Evolution (ICSME). 649--653.

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