Scientific Journal of KubSAU

One of the key problems facing medicine is the correct diagnosis given in a timely manner. For all the existence of medicine, humanity has accumulated a lot of knowledge in this area. According to this knowledge, new specialists are trained. But there is so much information that it is sometimes impossible to find the right information in it in time, and this can cost the person who came to see a doctor very expensive. In this specialist comes to the rescue computer. Information technologies, training in information bases perfectly cope with the task of identifying the disease and providing the most appropriate information

The creation of artificial intelligence systems is one of important and perspective directions of development of modern information technology. As there are many alternatives to artificial intelligence systems, there is a need to evaluate mathematical models of these systems. In this article, we consider a solution of the problem of identifying classes of levels of pay to employees on their characteristics. To achieve this goal it requires free access to test the source data and methodology, which will help to convert the data into the form needed for work in artificial intelligence systems. A good choice is a database of test problems for systems of UCI artificial intelligence repository. In this work we have used data base on teaching effectiveness for three regular semesters and two summer semesters of 151 teaching assistant (TA) assignments at the statistics Department of the University of Wisconsin-Madison. The most reliable in this application was the model of the INF4. The accuracy of the model in accordance with Lmeasure made up 0,809, which is much higher than the reliability of expert evaluations, which is equal to about 70%. To assess the reliability of the models in the ASC-analysis and in the system of "Eidos" we use F-criterion of van Ritbergen and its fuzzy multiclass generalization proposed by Professor E. V. Lutsenko