machine learning

Vibroartography is a method of medical diagnosis, designed for objective estimation of human joint motor function in general and arthrokinematics of the knee joint in particular. The method is based on the analysis of signals of vibroacoustic emission. Vibroartography is not so effective compared to methods such as radiography and magnetic resonance imaging (MRI), but it is definitely a sensitive method for assessing the degree of knee joint dysfunction. This paper presents the research results related to the design of a system for vibroarthrographic signals computer processing.

The paper considers the project of the system that carries out the bilateral process of search – candidate on a vacancy and automated search of vacancies for a candidate. For this purpose, information on available vacancies through web mining is constantly monitored. The obtained information on new vacancies is classified in terms of information related to previously defined classes of vacancies that play the role of a training sample.

The article describes the research of the peculiarities of methods and algorithms for the recognition of mathematical expressions. The possibility of simultaneous execution of structural analysis and classification of characters is investigated. The process of classification of the symbols and construction of the corresponding system, based on methods of machine learning, is described. The developed iterative algorithm is implemented in the design of the intelligent information system for the recognition of mathematical expressions.

In this article is considered the algorithm of logistic regression and construction of the neural network for the recognition of handwritten symbols in the image. Examples of implementation of two approaches for solving the problem of numerical recognition are given. The efficiency of using a neural network, as the provision of the most reliable recognition results, is explored.