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Alexander V. Medvedev
Daniil A. Melekh
Natalia A. Sergeeva
Olesya V. Chubarova
2020-01-20T07:15:03Z
2020-01-20T07:15:03Z
2019-09
Alexander V. Medvedev. Adaptive algorithm of classifcation on the missing data [Текст] / Alexander V. Medvedev, Daniil A. Melekh, Natalia A. Sergeeva, Olesya V. Chubarova // Applied Methods of Statistical Analysis Statistical Computation and Simulation. — 2019. — С. 292-298
http://amsa.conf.nstu.ru/amsa2019/proceedings/
https://elib.sfu-kras.ru/handle/2311/128728
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.
supervised learning
missing data
adaptive algorithm
nonparametric estimation of probability density
smoothing window
kernel function
numeric and nominal features
Adaptive algorithm of classifcation on the missing data
Journal Article
Journal Article Preprint
292-298
28.17.19
2020-01-20T07:15:03Z
Институт космических и информационных технологий
Кафедра информационных систем
Applied Methods of Statistical Analysis Statistical Computation and Simulation
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