Hierarchical Clustering of Features
This notebook explores the use of seriation to find an ordering of the features of a dataset that highlights a block struckture in the correlation matrix (blockmodeling). The approach shown here is based on the Pearson Correlation Coefficient, but can be taken as a basis in general for other correlation measures (e.g. distance correlation), or simply to reorder a distance matrix.