Machine learning applications in studies of the physical properties of active galactic nuclei based on photometric observations

Open Access

Fig. 14

Distributions of $λ_{{Edd}_{pred}}$ ${\lambda _{{\rm{Ed}}{{\rm{d}}_{{\rm{pred}}}}}}$ for various bins in $λ_{{Edd}_{true}}$ ${\lambda _{{\rm{Ed}}{{\rm{d}}_{true}}}}$ , in log space. Gaussian PDFs are fitted and shown over their respective histograms. The hatched area corresponds to the contamination between the lowest and highest range PDFs: the values quoted in Table 5 were calculated by dividing the overlapping (hatched area) with the integral of the highest range PDF.

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