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 betweenclusters 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 betweenclusters 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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