Name
Kostroma Dmitry Sergeevich
Scholastic degree
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Academic rank
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Honorary rank
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Organization, job position
Kuban State Agrarian University
Web site url
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Articles count: 2
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
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