| Software defect prediction using a cost sensitive decision forest and voting, and a potential solution to the class imbalance problem MJ Siers, MZ Islam Information Systems 51, 62-71, 2015 | 99 | 2015 |
| Cost sensitive decision forest and voting for software defect prediction MJ Siers, MZ Islam Pacific Rim International Conference on Artificial Intelligence, 929-936, 2014 | 17 | 2014 |
| Novel algorithms for cost-sensitive classification and knowledge discovery in class imbalanced datasets with an application to NASA software defects MJ Siers, MZ Islam Information Sciences 459, 53-70, 2018 | 13 | 2018 |
| Addressing Class Imbalance and Cost Sensitivity in Software Defect Prediction by Combining Domain Costs and Balancing Costs MJ Siers, MZ Islam Advanced Data Mining and Applications, 2016 | 10 | 2016 |
| Standoff-balancing: A novel class imbalance treatment method inspired by military strategy MJ Siers, MZ Islam Australasian Joint Conference on Artificial Intelligence, 517-525, 2015 | 6 | 2015 |
| RBClust: High quality class-specific clustering using rule-based classification MJ Siers, MZ Islam European Symposium on Artificial Neural Networks, Computational Intelligence …, 2016 | 4 | 2016 |
| Cost-Sensitive Decision Forest: CSForest MJ Siers, MZ Islam | 1 | 2015 |
| Class Imbalance and Cost-Sensitive Decision Trees: A Unified Survey Based on a Core Similarity MJ Siers, MZ Islam ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (1), 1-31, 2020 | | 2020 |
| Data Science for Class Imbalanced and Cost-Sensitive Data and its Application to Software Defect Prediction MJ SIERS CHARLES STURT UNIVERSITY, 2019 | | 2019 |
| WaterDM: A Knowledge Discovery and Decision Support Tool for Efficient Dam Management MZ Islam, M Furner, MJ Siers The 14th Australasian Data Mining Conference: AusDM 2016, 1-5, 2016 | | 2016 |
Professor Zahid IslamDirector of the Data Science Research Unit (DSRU)Verified email at csu.edu.au
