In the recent years the exponential growth of generation of textual documents and the emergent need to structure them increase the attention to the automated classification of documents into predefined categories. There is wide range of supervised learning algorithms that deal with text classification. KNN is one the most popular classifiers, simple to utilize and sufficiently effective. This paper deals with an approach for building a machine learning system in R that uses K-Nearest Neighbors (KNN) method for the classification of textual documents. The experimental part of the research was done on collected textual documents from two sources: http://egov.kz and http://www.government.kz.

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