Use of nonlinear feature transformations for extracting hidden patters in data

For finding hidden patterns in data analysis the nonlinear transformations, based on calculating the values of the class membership function for each feature, are used. The validity of the statement (hypothesis) is verified about the presence of sets of the features according to which the objects of classes based on generalized estimators will be correctly (without errors) divided on the numerical axis.