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Fig. 5.

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Plot of the feature importance calculated during the training process of the algorithm. The error bars are indicative of the standard deviation, providing insight into the stability of the feature importance estimates. The feature with the highest importance score in our diagnostic is EW(Hα), while all other features exhibit similar levels of relevance.

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