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This article is devoted to applying mathematical models in the differential diagnosis of venous diseases based on microwave radiometry data. A modified approach for transforming feature space in thermometric data is described. After constructing features, a multiclass classification problem is solved in several ways: by reducing to binary classification problems using "one versus rest" and "one versus one" methods and building a multivariate logistic regression model. The best classificationdoi:10.25209/2079-3316-2021-12-2-37-52 fatcat:trjxe6aphrepdc4rdomjnwjjxe