Finds the gradient of the variance ratio across the best hyperplane orthogonal to a given projection vector. Used to obtain maximum clusterability hyperplanes using gradient based optimisation.
df_mc(v, X, P)a numeric vector of length ncol(X)
a numeric matrix (num_data x num_dimensions) to be projected on v
a list of parameters including (at least) $nmin (positive integer minimum cluster size).
the (vector) gradient of the variance across the best hyperplane orthogonal to v.