Search alternatives:
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
based optimization » whale optimization (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary ai » binary _ (Expand Search), binary pairs (Expand Search)
ai based » i based (Expand Search), mri based (Expand Search), _ based (Expand Search)
learning optimization » learning motivation (Expand Search), lead optimization (Expand Search)
based optimization » whale optimization (Expand Search)
data learning » meta learning (Expand Search), deep learning (Expand Search), a learning (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
binary ai » binary _ (Expand Search), binary pairs (Expand Search)
ai based » i based (Expand Search), mri based (Expand Search), _ based (Expand Search)
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a) Accuracy and b) selected feature size of algorithms on the COVID-19 dataset.
Published 2022Subjects: -
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Boxplots analysis of the tested algorithms using average error rate across 21 datasets.
Published 2022Subjects: -
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Algorithm for generating hyperparameter.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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Results of machine learning algorithm.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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ROC comparison of machine learning algorithm.
Published 2024“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. To optimize the parameters of the machine learning algorithms, hyperparameter optimization with a genetic algorithm is proposed and to reduce the size of the feature set, feature selection is performed using binary grey wolf optimization algorithm. …”
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