Modeling of differential diagnosis classifiers of pathological states of the cardiovascular system
DOI:
https://doi.org/10.15587/1729-4061.2014.31079Keywords:
modeling, classifiers, logistic regression, discriminant analysis, group method of data handlingAbstract
The results of creating differential diagnosis classifiers of pathological states of the cardiovascular system are given in the paper. This task allows to solve the problem of creating non-invasive diagnosis method that allows to use repeated measurements, obtained in a state of unrest. A feature of this formulation is the classification of complex objects, each of which can overlap with other objects.
It is proposed to use the convolution of objects, obtained through the application of the modified combinatorial group method of data handling. Classification problem is solved by the "one-against-all" approach, i.e. a set of models, opposing each state to all other is modeled. The main purpose of the work was selecting the optimal modeling method, which allows to get the maximum accuracy on the training and test samples. As a result of the analysis, it was proved that the group method of data handling, which has shown the classification accuracy of over 90 % at the separation of all diagnoses is optimum for such problems.
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Copyright (c) 2014 Євген Арнольдович Настенко, Володимир Анатолійович Павлов, Олена Костянтинівна Носовець
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