An Ensemble Learning Algorithm Based on Resampling and Hybrid Feature Selection, with an Application to Software Defect Prediction-Reference-Cited by-同舟云学术

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An Ensemble Learning Algorithm Based on Resampling and Hybrid Feature Selection, with an Application to Software Defect Prediction

Published:2022-05 Issue: Volume: Page:
ISSN:
Container-title:2022 7th International Conference on Information and Network Technologies (ICINT)
language:
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Author:

Wei Wei¹,Jiang Feng¹,Yu Xu¹,Du Junwei¹

Affiliation:

1. Qingdao University of Science and Technology,Qingdao,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9939175/9939250/09939353.pdf?arnumber=9939353

Reference17 articles.

1. Attribute reduction based on granularity decision entropy;li;Computer and Modernization,2018

2. Parameter optimization of covariance random subspace method based on sensitivity analysis;liu;Engineering Mechanics,2021

3. Rough sets

4. Towards identifying software project clusters with regard to defect prediction

5. Summary of random forest algorithm;lv;Journal of the Hebei Academy of Sciences,2019

Cited by 1 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. FlexCon-CE: A Semi-supervised Method with an Ensemble-Based Adaptive Confidence;Intelligent Systems;2023

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