Statistical Recognition Method Based on Nonlinear Regression

作     者：Gavrikov, B.M. Gavrikov, M.B. Pestryakova, N.V. 

作者机构：Moscow City Oncology Hospital No. 62 Moscow Healthcare Department Moscow Russian Federation Keldysh Institute of Applied Mathematics Russian Academy of Sciences Moscow Russian Federation Federal Research Center Computer Science and Control Russian Academy of Sciences Moscow Russian Federation 

出 版 物：《Mathematical Models and Computer Simulations》 (Math. Models Comput. Simul.)

年 卷 期：2020年第12卷第6期

页      面：996-1004页

学科分类：07[理学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 070101[理学-基础数学] 

主　　题：body system classification handwritten symbol human health condition peripheral blood polynomial regression printed symbol recognition statistical method 

摘      要：Abstract: This study is devoted to the statistical method of classification based on nonlinear regression. The approaches used to implement it in solving the recognition problem of printed and handwritten characters are presented. Its implementation in assessing the health of the systems of the human body according to the parameters of peripheral blood is presented for the first time. The optimal structure of the polynomials is proposed. The properties of the probability estimates generated by the method are described. The structure of the sets used to train it is analyzed. © 2020, Pleiades Publishing, Ltd.