MICHAC: Defect Prediction via Feature Selection Based on Maximal Information Coefficient with Hierarchical Agglomerative Clustering-Reference-Cited by-同舟云学术

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MICHAC: Defect Prediction via Feature Selection Based on Maximal Information Coefficient with Hierarchical Agglomerative Clustering

Published:2016-03 Issue: Volume: Page:
ISSN:
Container-title:2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering (SANER)
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Author:

Xu Zhou,Xuan Jifeng,Liu Jin,Cui Xiaohui

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7476313/7476613/07476658.pdf?arnumber=7476658

Cited by 49 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. HFCCW: A Novel Hybrid Filter-Clustering-Coevolutionary Wrapper Feature Selection Approach for Network Anomaly Detection;International Journal of Machine Learning and Cybernetics;2024-05-18

2. Bridge temperature prediction method based on long short-term memory neural networks and shared meteorological data;Advances in Structural Engineering;2024-04-17

3. A Feature Selection Technique Using Self-Organizing Maps for Software Defect Prediction;Transactions on Computer Systems and Networks;2023-11-05

4. Software Defect Prediction Using Machine Learning Techniques;Advances in Artificial and Human Intelligence in the Modern Era;2023-09-08

5. ARRAY: Adaptive triple feature-weighted transfer Naive Bayes for cross-project defect prediction;Journal of Systems and Software;2023-08

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