Construction of a Compact and High-Precision Classifier in the Inductive Learning Method for Prediction and Diagnostic Problems

The study is dictated by the need to make reasonable decisions in classification of observations, for example, problems medical prediction and diagnostics. Today, as part digitalization healthcare, decision-making a doctor carried out using intelligent information systems. introduction such systems contributes implementation policies aimed at ensuring sustainable development health sector. paper discusses method inductive learning, which can be algorithmic basis In order build compact high-precision classifier studied method, it necessary obtain set informative patterns create building with high generalizing ability from this patterns. Three optimization models have been developed, are based on different concepts. Additionally, two procedures developed that used classifier. Experimental studies were diagnostics, finding best model pattern proving effectiveness procedures.