Prediction Based on the Solution of the Set of Classification Problems of Supervised Learning and Degrees of Membership

It is proposed to use the degrees of membership of objects to each class in the process of recognition in the linear corrector model to solve the problem of restoring dependences from precedent samples. Two models of the algorithm for calculating estimates are used as classifiers. The work of the proposed model is compared with the original method and with the well-known data analysis methods. The dependence of the work of the linear corrector on its parameters is studied.