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# Given a set of features, set up a weighted graph <math>G = (V, E)</math>, compute the weight of each edge, and summarize the information in <math>D</math> and <math>W</math>.
# Solve <math>(D - W)y = \lambda D y</math> for eigenvectors with the smallest eigenvalues.
# Use the eigenvector with the smallest eigenvalue to bipartition the graph (e.g. grouping according to sign).
# Decide if the current partition should be subdivided.
# Recursively partition the segmented parts, if necessary.
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