Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: Applied Methods of Statistical Analysis. Statistical Computation and Simulation - AMSA'2019; Novosibirsk; Novosibirsk
Год издания: 2019
Ключевые слова: supervised learning, missing data, adaptive algorithm, nonparametric estimation of probability density, smoothing window, kernel function, numeric and nominal features
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 chПоказать полностьюange 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.
Журнал: Applied Methods of Statistical Analysis. Statistical Computation and Simulation - AMSA'2019
Номера страниц: 292-298
Место издания: Novosibirsk
Издатель: Новосибирский государственный технический университет