I am wondering if feature agglomeration would work at all on heterogeneous features that have different ranges and also marginal distribution shapes. Feature agglomeration uses an Euclidean metric so it's very unlikely to work for those cases. Unless the features are normalized in some way using StandardScaler or a boxcox transform for instance?

I thought it would be worth mentioning this expected limitation in the doc.

@GaelVaroquaux what's your opinion on this?