Abstract: The effectiveness of machine learning (ML) and deep learning (DL) models on the Quora question pairs dataset is investigated in this study. ML models, including AdaBoost, reached 73.44% test accuracy, while ensemble learning approaches enhanced outcomes even further, with the Hard-Voting Ensemble achieving 76.13%. DL models, such as FCN, demonstrated test accuracy of 81% with cross validation. These findings contribute to natural language processing by demonstrating the potential of ensemble learning for ML models and the DL models' detailed pattern-capturing capacity.

Salsabil Tarek, Hatem M. Noaman and Mohammed Kayed, “Enhancing Question Pairs Identification with Ensemble Learning: Integrating Machine Learning and Deep Learning Models” International Journal of Advanced Computer Science and Applications(IJACSA), 14(11), 2023. http://dx.doi.org/10.14569/IJACSA.2023.01411100

@article{Tarek2023,
title = {Enhancing Question Pairs Identification with Ensemble Learning: Integrating Machine Learning and Deep Learning Models},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01411100},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01411100},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {11},
author = {Salsabil Tarek and Hatem M. Noaman and Mohammed Kayed}
}