feature importance should be normalised.

[cmacdonald]

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

100*feature_analysis.T[:,0]/np.max(feature_analysis.T[:,0])

[strani]

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.

[cmacdonald]

@strani I think the normalisation as an option is a good idea. I find the numbers much more interpretable in normalised form.

Craig