[15], type I error (alpha) = 0.01 and power of study of 90%, the sample size calculated by using PS software [16] was 242 with each arm of 121 intervention group and control group. Anticipating dropout rate to be 20%, the final sample size was 290 (145 each for intervention and ...
To prevent overfitting, we implemented max-norm regularization (bounding the norms of the weights and biases to be less than 3) and dropout [54] in each hidden layer. Adam [55] was used as optimizer, and early stopping was applied to further improve generalization performance [56]. 2.3.3...