The Learning System by the Least Squares Support Vector Machine Method and its Application in Medicine

Authors

DOI:

https://doi.org/10.26636/jtit.2011.3.1165

Keywords:

classification, Grid-Search, Particle Swarm Optimization, patients diagnosis, Support Vector Machine

Abstract

In the paper it has been presented the possibility of using the least squares support vector machine to the initial diagnosis of patients. In order to find some optimal parameters making the work of the algorithm more detailed, the following techniques have been used: K-fold Cross Validation, Grid-Search, Particle Swarm Optimization. The result of the classification has been checked by some labels assigned by an expert. The created system has been tested on the artificially made data and the data taken from the real database. The results of the computer simulations have been presented in two forms: numerical and graphic. All the algorithms have been implemented in the C# language.

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Submitted

2023-06-28

Published

2011-09-30

Issue

Section

RESEARCH ARTICLES

How to Cite

[1]
P. Szewczyk and M. Baszun, “The Learning System by the Least Squares Support Vector Machine Method and its Application in Medicine”, JTIT, vol. 45, no. 3, pp. 109–113, Sep. 2011, doi: 10.26636/jtit.2011.3.1165.