An Adaptive Approach for defect Prediction using Dynamic Classifiers Selection
Author:
Affiliation:
1. Microsoft,Hyderabad,Telangana,India
2. Indian Institute of Technology (BHU),Department of Computer Science and Engineering,Varanasi,UP,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10059457/10059586/10059946.pdf?arnumber=10059946
Reference22 articles.
1. Class Imbalance Issue in Software Defect Prediction Models by various Machine Learning Techniques: An Empirical Study
2. An empirical study toward dealing with noise and class imbalance issues in software defect prediction;kumar;Soft Computing,2021
3. An investigation on the feasibility of cross-project defect prediction
4. Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings
5. DNNAttention: A deep neural network and attention based architecture for cross project defect number prediction
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