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UniFIeD Univariate Frequency-based Imputation for Time Series Data

  • This paper introduces UniFIeD, a new data preprocessing method for time series. UniFIeD can cope with large intervals of missing data. A scalable test function generator, which allows the simulation of time series with different gap sizes, is presented additionally. An experimental study demonstrates that (i) UniFIeD shows a significant better performance than simple imputation methods and (ii) UniFIeD is able to handle situations, where advanced imputation methods fail. The results are independent from the underlying error measurements.

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Metadaten
Author:Martina Friese, Jörg Stork, Ricardo Ramos Guerra, Thomas Bartz-BeielsteinGND, Soham Thaker, Oliver Flasch, Martin Zaefferer
URN:urn:nbn:de:hbz:832-cos-493
ISBN:2194-2870
Series (Serial Number):CIplus (5/2013)
Document Type:Report
Language:English
Year of Completion:2013
Release Date:2013/10/16
Tag:Fehlende Daten; Zeitreihenanalyse
Imputation; Missing Data; Time-series
GND Keyword:Datenanalyse; Prognose; Vorverarbeitung; Zeitreihe
Institutes and Central Facilities:Fakultät für Informatik und Ingenieurwissenschaften (F10) / Fakultät 10 / Institut für Informatik
Dewey Decimal Classification:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
Open Access:Open Access
Licence (German):License LogoCreative Commons - Namensnennung, Nicht kommerziell, Keine Bearbeitung