Abstract—A procedure for classifying objects with a hierarchical structure of relations (se-
mantics) of features that takes into account their modalities is proposed. The concepts of
semantics of features and their modalities are explained prior to the description of this pro-
cedure. A three-level model with a semantic hierarchy of features (objects—meta-features—
subfeatures of objects) is considered. Meta-features are interpreted as semantic generalizations
of the related subfeatures of objects. An important stage of the proposed procedure is the
aggregation of the lower level subfeatures, taking into account their semantic connection with
the meta-features. Aggregation leads to a significant reduction in the dimension of the original
classification problem, which is now solved in terms of values of the aggregation function. As
an example, the Dermatology sample from the well-known UCI Machine Learning repository is
considered. This example shows that despite a considerable imbalance of the Dermatology sam-
ple, the results yielded by the proposed procedure are quite comparable with the best results
of some well-known algorithms obtained on this sample.