Optimizing Deep Learning Model Parameters with the Bees Algorithm for Improved Medical Text Classification
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 the Bees Algorithm, and 88
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