BOOK-CHAPTER
Cost Sensitive Decision Forest and Voting for Software Defect Prediction
Michael J. SiersMd Zahidul Islam
Year: 2014 Lecture notes in computer science Pages: 929-936 Publisher: Springer Science+Business Media
Keywords:
Computer science Voting Decision tree Classifier (UML) Data mining Software Machine learning Majority rule Random forest Artificial intelligence
Metrics
16
Cited By
1.54
FWCI (Field Weighted Citation Impact)
14
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%
Citation History
Topics
Software Engineering Research
Physical Sciences → Computer Science → Information Systems
Imbalanced Data Classification Techniques
Physical Sciences → Computer Science → Artificial Intelligence
Machine Learning and Data Classification
Physical Sciences → Computer Science → Artificial Intelligence
Related Documents
JOURNAL ARTICLE
Software defect prediction using a cost sensitive decision forest and voting, and a potential solution to the class imbalance problem
Michael J. SiersMd Zahidul Islam
Journal: Information Systems Year: 2015 Vol: 51 Pages: 62-71
BOOK-CHAPTER
Software Defect Prediction Method Based on Cost-Sensitive Random Forest
Weidong ZhaoShengdong ZhangMing Wang
IFIP advances in information and communication technology Year: 2022 Pages: 369-381
JOURNAL ARTICLE
Misclassification Cost-Sensitive Software Defect Prediction
Ling XuWang BeiLing LiuMo ZhouShengping LiaoMeng Yan
Year: 2018 Pages: 256-263
JOURNAL ARTICLE
Cost Sensitive Boosting Software Defect Prediction Method
LI Li, REN Zhenkang, SHI Kexin
Journal: DOAJ (DOAJ: Directory of Open Access Journals) Year: 2022
JOURNAL ARTICLE
Cost-sensitive Dictionary Learning for Software Defect Prediction
Liang NiuJianwu WanHongyuan WangKaiwei Zhou
Journal: Neural Processing Letters Year: 2020 Vol: 52 (3)Pages: 2415-2449