Entropy-based evaluation in classification problems

The problem of binary classification is considered, an algorithm for its solution based on maximum entropy estimation of the parameters of randomized data models is offered: a detailed description of the model and the entropy estimation method is given, advantages and disadvantages of this approach are described, the results of numerical experiments and comparisons with the classical support vector machine algorithm on the accuracy of classification and depending on the volume of the training sample.