Enhancing Question Pairs Identification with Ensemble Learning: Integrating Machine Learning and Deep Learning Models
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 ac...
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| Veröffentlicht in: | International journal of advanced computer science & applications 2023, Vol.14 (11) |
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| container_title | International journal of advanced computer science & applications |
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| creator | Tarek, Salsabil Noaman, Hatem M. Kayed, Mohammed |
| description | 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. |
| doi_str_mv | 10.14569/IJACSA.2023.01411100 |
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| ispartof | International journal of advanced computer science & applications, 2023, Vol.14 (11) |
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| subjects | Accuracy Algorithms Artificial intelligence Classification Comparative analysis Computer science Datasets Deep learning Ensemble learning Investigations Language Machine learning Natural language processing Neural networks Performance evaluation Questions Search engines Semantics Software Text categorization |
| title | Enhancing Question Pairs Identification with Ensemble Learning: Integrating Machine Learning and Deep Learning Models |
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