Fig. 7: Hyperparameter optimization for age estimation using FNN, LSTM, and Inception-1D models.
From: Age estimation via electrocardiogram from smartwatches
FNN: MAE vs a number of hidden units, b Number of hidden layers, c learning rate, d batch size, e epochs, f dropout rate, g input feature length. LSTM: MAE vs h number of LSTM layers, i number of hidden units, j input sequence length, k learning rate, l batch size, m epochs, n dropout rate. Inception-1D: MAE vs o number of inception blocks, p number of filters per block, q input sequence length, r learning rate, s batch size, t Epochs, u dropout rate.
