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@article{186551,
        author = {Anil Purushothaman and Varsha Jotwani},
        title = {Enhancing Academic Grade Prediction Through Bat Algorithm- Driven Ensemble Learning Technique},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {1034-1049},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186551},
        abstract = {In this paper, we present an ensemble framework utilizing the Bat Algorithm for predicting the student academic performance in two parts of the course, that is at 40% and 80% course completion. The model achieves an optimal feature selection using the Bat Algorithm and the bagging ensemble integrates four distinct classification algorithms: K-Nearest Neighbors, Support Vector Machine, XGBoost, and Long Short-Term Memory LSTM. We evaluate the addition of PCA to this ensemble, considering the trade-off between dimensionality reduction and classification performance.},
        keywords = {Academic performance prediction, Bat Algorithm, ensemble learning, multi-class classification, feature selection, higher education.},
        month = {November},
        }