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I ended up adding a normalize parameter, which is True by default, that normalizes the given importances in the range [0,1]. I preferred that way instead of multiplying the values by 100 (supposed to be a percentage). Obtaining the 100 based value is however straightforward.
P.S. LightGBM and XGBoost do not normalize feature importance, according to the documentation.
It is customary to normalise them to be 100 max. See Hastie et al. pg 368:
https://web.stanford.edu/~hastie/Papers/ESLII.pdf
I used
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