Suneel Kumar Rath1, Madhusmita Sahu1, Shom Prasad Das2, Junali Jasmine Jena3, Chitralekha Jena4, Baseem Khan5,6,7,*, Ahmed Ali7, Pitshou Bokoro7
Computer Systems Science and Engineering, Vol.48, No.6, pp. 1513-1536, 2024, DOI:10.32604/csse.2024.057067
- 22 November 2024
Abstract Redundancy, correlation, feature irrelevance, and missing samples are just a few problems that make it difficult to analyze software defect data. Additionally, it might be challenging to maintain an even distribution of data relating to both defective and non-defective software. The latter software class’s data are predominately present in the dataset in the majority of experimental situations. The objective of this review study is to demonstrate the effectiveness of combining ensemble learning and feature selection in improving the performance of defect classification. Besides the successful feature selection approach, a novel variant of the ensemble learning… More >
Login
Register
