Journals & Conferences
- Rojarath, A., Songpan, W., & Surinta, O. (2025). Depression Classification with Imbalanced Data Problems: Literature Survey, Engineering Access, 11(2), 185-199. https://doi.org/10.14456/mijet.2025.18
- Rojarath, A., Songpan, W., Okafor, E., & Surinta, O. (2025). Enhancing Personality Characteristics Analysis with SMOTE and Association Rule Mining: A Case Study on Introverts and Extroverts, ICIC Express Letters, 19(6), 597-606. https://doi.org/10.24507/icicel.19.06.597
- Khamket, T., Polpinij, Jantima., Rojarath, A., Luaphol, B. (2025). Enhancing Sentiment Classification: A Comparative Analysis of Supervised and Unsupervised Methods for Improving Training Data Quality, ICIC Express Letters, Part B: Applications, 16(5), 471-479. https://doi.org/10.24507/icicelb.16.05.471
- Sarawan, K., Polpinij, J., Somprasertsri, G., Rojarath, A., Luaphol, B. (2025). Multiclass Classification Approach for Detecting Software Bug Severity Level from Bug Reports, ICIC Express Letters, Part B: Applications, 16(5), 567-576. https://doi.org/10.24507/icicelb.16.05.567
- Rojarath, A., Jantama, T., Srirat, W., Mookpakdee, N., khumwiso, K., & Surinta, O. (2024). Factors analysis affecting stroke disease using association rules. Journal of Science and Technology Mahasakham University, 43(3), 206-222. (TCI 1) [In Thai]
- Rojarath, A., & Songpan, W. (2021). Cost-sensitive probability for weighted voting in an ensemble model for multi-class classification problems. Applied Intelligence, 51(7), 4908–4932. https://doi.org/10.1007/s10489-020-02106-3
- Rojarath, A., & Songpan, W. (2020). Probability-Weighted Voting Ensemble Learning for Classification Model. Journal of Advances in Information Technology, 11(4), 217–227. https://doi.org/10.12720/jait.11.4.217-227
- Rojarath, A., Songpan, W., & Pong-inwong, C. (2016). Improved ensemble learning for classification techniques based on majority voting. 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS). https://doi.org/10.1109/ICSESS.2016.7883026
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