A classification algorithm based on ensembles of nonparametric models

The paper deals with a classification strategy which utilises nonparametric modeling of a decision rule in a case of large feature vector length and large sample volume. An algorithm of collective assessment of k-nearest neighbors is proposed, which significantly reduces the computational cost. The work of algorithm is demonstrated on one application problem.