Table 1.

Deep learning models selected hyperparameters used during training

Model	Hyperparameters
MiniRocket	Number of features: 10000; Maximum dilations per kernel: 16; scoring: MSE
ResNet	Windows size = 24, filter size = 32, kernel sizes: 7, 5 and 4
XceptionTime	Filter size = 16, adaptive average pooling: 32
InceptionTime	Filter size = 32, kernel sizes: 24, depth : 6; dilation: 1
Transformer	Windows size = 24, embedding size: 32, Size of the intermediate
	feed forward layer:16, number of layers: 2 and number of heads: 4