Fig. 10


Contribution of the different lines (both integrated intensity and temperature peak) to the quality of the random forest fit of the training data set. Noise #1 and 2 are two additional random sets of input data. Top: quantitative improvement of the quality of the fit (RMSE feature importance) for each available line. Bottom: evolution of the RMSE (filled circles) and maximum absolute error when each line is progressively added into the training phase in the order defined in the top panel. These results are computed on the training set. The RMSE values on each diagram are commensurate to log .

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