  The article deals with the issue of modification of metric classification
algorithms. In particular, it studies the algorithm k-Nearest Neighbours for
its application to sequential data. A method of generalization of metric
classification algorithms is proposed. As a part of it, there has been
developed an algorithm for solving the problem of classification and labelling
of sequential data. The advantages of the developed algorithm of classification
in comparison with the existing one are also discussed in the article. There is
a comparison of the effectiveness of the proposed algorithm with the algorithm
of CRF in the task of chunking in the open data set CoNLL2000.
