Copy For Citation
ÖZTÜRK KIYAK E., BİRANT D., BİRANT K. U.
E-INFORMATICA SOFTWARE ENGINEERING JOURNAL, vol.15, no.1, pp.163-184, 2021 (ESCI)
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Publication Type:
Article / Article
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Volume:
15
Issue:
1
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Publication Date:
2021
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Doi Number:
10.37190/e-inf210108
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Journal Name:
E-INFORMATICA SOFTWARE ENGINEERING JOURNAL
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Journal Indexes:
Emerging Sources Citation Index (ESCI), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, Directory of Open Access Journals
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Page Numbers:
pp.163-184
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Keywords:
Software defect prediction, multi-view learning, machine learning, k-nearest neighbors, MULTITASK, MODEL, KNN
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Dokuz Eylül University Affiliated:
Yes
Abstract
Background: Traditionally, machine learning algorithms have been simply applied for software defect prediction by considering single-view data, meaning the input data contains a single feature vector. Nevertheless, different software engineering data sources may include multiple and partially independent information, which makes the standard single-view approaches ineffective.