A Symptom Selection Algorithm Based on Classification Errors
Akhram Kh. NishanovTashkent University of Information Technologies named after Muhammad al-Khwarizmi, Software Engineering Faculty, Tashkent, UzbekistanBakhtiyorjon AkbaralievTashkent University of Information Technologies named after Muhammad al-Khwarizmi, Software Engineering Faculty, Tashkent, UzbekistanG.P. DjurayevTashkent University of Information Technologies named after Muhammad al-Khwarizmi, Scientific and Innovation Center of Information and Communication Technologies, Tashkent, Uzbekistan
2020 International Conference on Information Science and Communications Technologies (ICISCT)conference2020en
Ochiq kirish: yoʻq
ABI
Annotatsiya
In this paper the issues like preprocessing of ischemic heart disease data and optimization of feature space are discussed and solved. Here an algorithm for selection a set of information features based on classification error are proposed. Using this algorithm was obtain the set of most informative symptoms for three class of ischemic heart disease: “Progressive angina pectoris”, “Acute myocardial infarction” and “Arrhythmic form”.
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