Missing Data Analysis in Regression

Many of the datasets in real-world applications contain incompleteness. In this paper, we approach the effects and possible solutions to incomplete databases in regression, aiming to bridge a gap between theoretically effective algorithms. We investigated the actual effects of missing data for regre...

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Veröffentlicht in:	Applied artificial intelligence 2022-12, Vol.36 (1)
Hauptverfasser:	Marcelino, C. G., Leite, G. M. C., Celes, P., Pedreira, C. E.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Data analysis Datasets Decision trees Impact analysis Missing data Neural networks Regression Support vector machines
Online-Zugang:	Volltext
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