Cross-company defect prediction via semi-supervised clustering-based data filtering and MSTrA-based transfer learning
- 8 March 2018
- journal article
- research article
- Published by Springer Nature in Soft Computing
- Vol. 22 (10) , 3461-3472
Abstract
No abstract availableKeywords
Funding Information
- National Natural Science Foundation of China (61070013)
This publication has 40 references indexed in Scilit:
- Multi-objective cross-version defect predictionSoft Computing, 2016
- Improving Relevancy Filter Methods for Cross-Project Defect Prediction2015
- A Hybrid Instance Selection Using Nearest-Neighbor for Cross-Project Defect PredictionJournal of Computer Science and Technology, 2015
- Software defect prediction using cost-sensitive neural networkApplied Soft Computing, 2015
- A systematic review of machine learning techniques for software fault predictionApplied Soft Computing, 2015
- The use of decision trees for cost‐sensitive classification: an empirical study in software quality predictionWIREs Data Mining and Knowledge Discovery, 2011
- Software Defect Prediction Using Fuzzy Support Vector Regression2010
- On the relative value of cross-company and within-company data for defect predictionEmpirical Software Engineering, 2009
- Using the Support Vector Machine as a Classification Method for Software Defect Prediction with Static Code Metrics2009
- Naive (Bayes) at forty: The independence assumption in information retrieval1998