Optimizing Deep Learning Model Parameters with the Bees Algorithm for Improved Medical Text Classification
Abstract
This paper introduces a novel mechanism to obtain the optimal parameters of a deep learning model using the Bees Algorithm, which is a recent promising swarm intelligence algorithm. The optimization problem is to maximize the accuracy of classifying ailments based on medical text given the initial hyper-parameters to be adjusted throughout a definite number of iterations. Experiments included two different datasets: English and Arabic. The highest accuracy achieved is 99.63% on the English dataset using Long Short-Term Memory (LSTM) along with the Bees Algorithm, and 88% on the Arabic dataset using AraBERT.
- Publication:
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arXiv e-prints
- Pub Date:
- March 2023
- DOI:
- 10.48550/arXiv.2303.08021
- arXiv:
- arXiv:2303.08021
- Bibcode:
- 2023arXiv230308021S
- Keywords:
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- Computer Science - Computation and Language;
- Computer Science - Artificial Intelligence