of size 64$\times$64. The GAF MTF, and RP encodings have by definition a resulting image size equal to that of the input time series. Therefore, we downscale the resulting images using average pooling.

In the following, the hyperparameter settings for the selected encodings are described.

**GAF:** The GAF only has a single parameter to tune, which is the clipping parameter that determines the allowable upper and lower boundaries for time series values. Following the work in [@beirlant2006statistics], we find a linear relationship in the QQ-plot of the training dataset. By extrapolation, we find that the probability to observe a value beyond $1.2$ times the max or the min of $X$ is numerically equal to $0$. We choose therefore these values as the upper and lower bounds $\mathrm{UB}$ and $\mathrm{LB}$. Values exceeding this threshold in the test set are clipped.

**MTF:** The MTF also depends only on one parameter being the number of bins which determines the resolution of the value grid. In this case, 500 bins for SAX algorithm showed a good trade-off between capturing relevant patterns, excluding noise and computational burden.

**RP:** The subsection length is fixed at 1 in order to avoid loosing information and to achieve the 