  This paper describes a new approach to the problem of the structural research
of clusters based on the theory of geodetic and k-geodetic graphs. We firmly
believe that this same approach can be used when solving problems of
correlation between structural and spectral metrics in complex networks. So,
what we want to point out is about the possibility of applying one theory of
networks (the theory of k-geodetic networks) to the solution of problems in
another type of networks (complex networks). The theory of geodetic graphs and
their various modifications represents an important tool for the structural
analysis of complex systems of transmission, processing, and analysis of
information. In the case of large data sets, their stochastic dependence is
described by large-dimensional correlation matrices. One of the problems of
correlation analysis is the study of the structure of the correlation matrix.
It is proved that such a structure is adequately described by geodetic graphs.
The obtained structural data allow solving the choice problem of significant
variables in multidimensional regression models.
