A Symptom Selection Algorithm Based on Classification Errors
Akhram Kh. Nishanov, Bakhtiyorjon Akbaraliev, G.P. Djurayev · 2020 International Conference on Information Science and Communications Technologies (ICISCT) · 2020
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”.