Description Usage Arguments Details Value
This function finds the best binary question do divide a cluster A into to subclusters such that the bipartition (A_l, A_l_c) has maximum between-clusters inertia.
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X |
the data matrix of dimension (nxp) where p is equal to the number of numerical variables plus the number of categories. This matrix is used to construct the binary questions |
Z |
the numerical data matrix of dimension (nxk) used to compute the inertia criterion (the matrix of the principal components for instance) |
indices |
vector of indices for the cluster A to divide. |
vec_quali |
vector containing the number of categories for each modalities (according to the categories observed in A_l) |
w |
weights vector |
D |
diagonal distance matrix coefficients |
vec_order |
vector containing TRUE if the categories of the variable are ordered |
This function works for both categorical, numerical and mixed data. This is the core function of the divclust algorithm. We are seeking the binary question which gives the best bipartition. A binary question is defined with a cutting variable (quantitative or qualitative), and a cutting value. For quantitative variable, the cutting value is a real number. For qualitative, the cutting value is
inert |
the between-clusters inertia of the bipartition (A_l, A_l_c) |
A_l |
the vector of indices of the cluster A_l |
A_l |
the vector of indices of the cluster A_l_c |
cut_ind |
the index of the cutting variables |
cut_val |
a list with :
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