Abstarct

The problem of reconstructing dependencies from empirical data became very
important in a very large range of applications. Procedures used to solve this
problem are known as "Methods of Machine Learning". These procedures
include methods of regression reconstruction, inverse problems of mathematical
physics and statistics, machine learning in pattern recognition (for visual and
abstract patterns represented by sets of features) and many others. Many web
network control problems also belong to this field. The task is to reconstruct
the dependency between input and output data as precisely as possible using
empirical data obtained from experiments or statistical observations.