Computing Importance Value of Medical Data Parameters in Classification Tasks and Its Evaluation Using Machine Learning Methods
This paper aims to evaluate the importance values of medical data parameters for further classification tasks. One of the steps of proposed methodology for analyzing medical data is initial data analysis. One part of the initial data analysis is to determine the importance rate of parameters in given data set. The reason behind this step is to provide overview of the parameters and the idea of choosing right predictors for classification task. Statistica 13 software provides a tool for determining the importance rate of each data parameter, which can be found in feature selection module. However, it is not always clear whether is the importance rate correct or not.
KeywordsData analysis Classification Predictors
This publication is the result of implementation of the project: “UNIVERSITY SCIENTIFIC PARK: CAMPUS MTF STU - CAMBO” (ITMS: 26220220179) supported by the Research & Development Operational Program funded by the EFRR.
This publication is the result of implementation of the project VEGA 1/0673/15: “Knowledge discovery for hierarchical control of technological and production processes” supported by the VEGA.
This publication was written with the financial support of the KEGA agency in the frame of the project 040STU-4/2016 “Modernization of the Automatic Control Hardware course by applying the concept Industry 4.0”.
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