I would add a comment that this kind of preprocessing only suited for data with homogeneous features such as pixel intensities in computer vision or gene expression levels in biology. It does not really make sense to use it on heterogeneous features (e.g. feature reflecting different physical quantities such as a price in U.S. dollars and a temperature in degrees Celsius): the agglomeration uses a euclidean metric to find related features and furthermore compute average values between feature values at transform time. Averaging heterogeneous feature values does not really make sense IMHO.