Method of weighted discriminant systems for the classification of objects with missing data

The authors describe a method of classification of objects with missing or partially known data. The tasks related to the processing of incomplete data are common in medicine. Patient data can contain gaps or missing. Information classification of patients with varying degrees of schizophrenia was carried out using the new method. Schizophrenia is a genetic disease; so, important is the task of studying the genetic predisposition of a person to the disease. Analysis of associations between polymorphisms of genes was performed. A distinctive feature of the provision of medical data is its emptiness by more than 70%. The dimension of discriminant signs was significantly reduced and high reliability of forecasting has been received.