Cost Sensitive Decision Forest and Voting for Software Defect Prediction. - Michael J. Siers; Md Zahidul Islam 001 (PRICAI, 2014)

Standoff-Balancing: A Novel Class Imbalance Treatment Method Inspired by Military Strategy. - Michael J. Siers; Md Zahidul Islam 001 (Australasian Conference on Artificial Intelligence, 2015)

Software defect prediction using a cost sensitive decision forest and voting, and a potential solution to the class imbalance problem. - Michael J. Siers; Md Zahidul Islam 001 (Inf. Syst., 2015)

Addressing Class Imbalance and Cost Sensitivity in Software Defect Prediction by Combining Domain Costs and Balancing Costs. - Michael J. Siers; Md Zahidul Islam 001 (ADMA, 2016)

RBClust: High quality class-specific clustering using rule-based classification. - Michael J. Siers; Md Zahidul Islam 001 (ESANN, 2016)

Novel algorithms for cost-sensitive classification and knowledge discovery in class imbalanced datasets with an application to NASA software defects. - Michael J. Siers; Md Zahidul Islam 001 (Inf. Sci., 2018)

Class Imbalance and Cost-Sensitive Decision Trees: A Unified Survey Based on a Core Similarity. - Michael J. Siers; Md Zahidul Islam 001 (ACM Trans. Knowl. Discov. Data, 2021)