Data-efficient software defect prediction: A comparative analysis of active learning-enhanced models and voting ensembles-Reference-Cited by-同舟云学术

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Data-efficient software defect prediction: A comparative analysis of active learning-enhanced models and voting ensembles

Published:2024-08 Issue: Volume:676 Page:120786
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Liapis Charalampos M.^ORCID,Karanikola Aikaterini^ORCID,Kotsiantis Sotiris

Publisher

Elsevier BV

Reference48 articles.

1. Active Learning Literature Survey;Settles,2009

2. A survey on cost types, interaction schemes, and annotator performance models in selection algorithms for active learning in classification;Herde;IEEE Access,2021

3. Ensemble learning;Sewell;RN,2008

4. Measures of diversity in classifier ensembles and their relationship with the ensemble accuracy;Kuncheva;Mach. Learn.,2003

5. Dealing with imbalanced data for interpretable defect prediction;Gao;Inf. Softw. Technol.,2022

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