Effective multi-objective naïve Bayes learning for cross-project defect prediction

Author:

Ryu Duksan,Baik Jongmoon

Funder

National Research Foundation of Korea

Korea government

Institute for Information & communications Technology Promotion

Publisher

Elsevier BV

Subject

Software

Reference40 articles.

1. Learning from imbalanced data;He;IEEE Trans. Knowl. Data Eng.,2009

2. On the relative value of cross-company and within-company data for defect prediction;Turhan;Empir. Softw. Eng.,2009

3. A new heuristic optimization algorithm: harmony search;Geem;Simulation,2001

4. Towards identifying software project clusters with regard to defect prediction;Jureczko;Proc. 6th Int. Conf. Predict. Model. Softw. Eng.—PROMISE’10,2010

5. The PROMISE Repository of empirical software engineering data;Menzies,2012

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