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Predicting the global far-infrared SED of galaxies via machine learning techniques

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Academic year: 2021

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Figure

Fig. 1. Diagram of the pipeline, split into six steps. The red boxes are used for input data, which do not make use of Herschel
Fig. 2. Predicted vs true values, for the sample of 4333 galaxies (H-ATLAS + DustPedia)
Fig. 3. Similar to Fig. 2, but for the neural network prediction. Instead of ME, which was always very small, we show R 2 (Eq
Fig. 4. Misprediction error (ˆ y − y) as a function of the predicted uncertainty. The values for all Herschel bands are plotted on this figure, so each galaxy in the sample has six data points on this plot
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