Using Coding-Based Ensemble Learning to Improve Software Defect Prediction

Software Fault Prediction Using Quad Tree-Based K-Means Clustering Algorithm

(2011) Partha S. Bishnu et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches

(2011) M. Galar et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE

A General Software Defect-Proneness Prediction Framework

(2010) Qinbao Song et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Cost-sensitive boosting neural networks for software defect prediction

(2009) Jun Zheng   EXPERT SYSTEMS WITH APPLICATIONS

Learning from Imbalanced Data

(2009) Haibo He et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Evolutionary Sampling and Software Quality Modeling of High-Assurance Systems

(2009) D.J. Drown et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS

Improving Software-Quality Predictions With Data Sampling and Boosting

(2009) C. Seiffert et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS

RUSBoost: A Hybrid Approach to Alleviating Class Imbalance

(2009) Chris Seiffert et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS

Analysis of Naive Bayes’ assumptions on software fault data: An empirical study

(2008) Burak Turhan et al.   DATA & KNOWLEDGE ENGINEERING

Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings

(2008) S. Lessmann et al.   IEEE TRANSACTIONS ON SOFTWARE ENGINEERING

Exploratory Undersampling for Class-Imbalance Learning

(2008) Xu-Ying Liu et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS