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Table 2 The ranges of parameters in hyperparameter optimization

From: A computational clinical decision-supporting system to suggest effective anti-epileptic drugs for pediatric epilepsy patients based on deep learning models using patient’s medical history

Parameters

Range

Number of channels

[1, 2, 3, 4, 5]

Filter size

[2, 3, 4, 5, 6, 7, 8, 10]

Values of dropout

[0.2, 0.3, 0.4, 0.5]

Learning rate

[0.0005, 0.0001, 0.005, 0.001, 0.05, 0.01]

Epochs

[32, 50, 64, 100, 128, 150]

Batch sizes

[16, 32, 64, 128]

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BMC Medical Informatics and Decision Making

ISSN: 1472-6947

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