FIGURE 1.

Comparison design. Each model is configured by a set of learning parameters and supplied features, either raw signal or wavelet scattering features that were generated from waveform records with different window sizes and step lengths. The analyzed values of the window size ranged from 0.5 to 5 s, and the step sizes ranged from 0.1 s to the value of the window size. An example of the segmentation of waveform records is shown in Figure 2B. A total of 11 models were compared, including generalized linear regression, ridge regression, lasso regression, stochastic gradient descent regression, support vector machine regression, nearest neighbors regression, Gaussian process regression, random forest regression, extremely randomized trees regression, extreme gradient boosting tree regression, and residual convolutional neural network.