1. A method, comprising: performing, by a processing device, a semantico-syntactic analysis of a natural language text of a corpus of natural language texts to produce a semantic structure representing a set of semantic classes; identifying a natural language text feature to be extracted from the semantic structure using a set of values of a plurality of feature extraction parameters; partitioning the corpus of natural language texts into a training data set comprising a first plurality of natural language texts and a validation data set comprising a second plurality of natural language texts; determining, in view of the category of the training data set, the set of values of the feature extraction parameters, by optimizing a function reflecting a number of natural language texts of the validation data set that are classified correctly by the text classifier model using the set of values of the feature extraction parameters; and classifying the natural language text by applying the text classifier model using the set of values of the feature extraction parameters.