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I did Clustering with K-MEANS model and I wish to understand how the variables importance percentages in the histogram are calculated? what does it measure?

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We fit a simple random forest supervised model to the output classes of the kmeans. This allows us to derive variable importances, as per the random forest standard method (implemented in scikit-learn).
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I can see a feature with 10%,  another is 5%. What is the meaning of % in variable importances?
We use the definition of variable importance in percentage from the random forest model in scikit-learn.
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