Adaptive algorithm of classifcation on the missing data

Alexander V. Medvedev; Daniil A. Melekh; Natalia A. Sergeeva; Olesya V. Chubarova

Adaptive algorithm of classifcation on the missing data

Alexander V. Medvedev, Daniil A. Melekh, Natalia A. Sergeeva, Olesya V. Chubarova

Дата публикации: 2019-09

Дата публикации в реестре: 2020-06-02T17:14:58Z

Аннотация:

The problem of classi cation by data with gaps, bypassing the stage of their lling, is considered. An adaptive restructuring of algorithms is proposed as a result of the introduction of corresponding indicators into them. The indicators take into account the ow of current information, on the basis of which a decision is made to change the algorithm and the data processing technology itself at each cycle. Computational procedures are based on non-parametric estimation, are given their settings and the results of numerical modeling. Сборник проходит регистрацию в базе Scoupus.

Ключевые слова:
supervised learning, missing data, adaptive algorithm, nonparametric estimation of probability density, smoothing window, kernel function, numeric and nominal features, 28.17.19

Тип: Journal Article