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.

中文翻译：

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基于非线性回归的统计识别方法

摘要

本研究致力于基于非线性回归的分类统计方法。提出了解决印刷和手写字符识别问题的方法。首次介绍了其在根据外周血参数评估人体系统健康方面的实现。提出了多项式的最优结构。描述了通过该方法生成的概率估计的属性。分析用于训练它的集合的结构。