  The article presents a method that improves the quality of classification of
objects described by a combination of known and unknown features. The method is
based on modernized Informational Neurobayesian Approach with consideration of
unknown features. The proposed method was developed and trained on 1500 text
queries of Promobot users in Russian to classify them into 20 categories
(classes). As a result, the use of the method allowed to completely solve the
problem of misclassification for queries with combining known and unknown
features of the model. The theoretical substantiation of the method is
presented by the formulated and proved theorem On the Model with Limited
Knowledge. It states, that in conditions of limited data, an equal number of
equally unknown features of an object cannot have different significance for
the classification problem.
