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.
| 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: | Zeitreihe; Prognose; Datenanalyse; Vorverarbeitung |
| Institutes and Central Facilities: | Fakultät für Informatik und Ingenieurwissenschaften (F10) / Fakultät 10 / Institut für Informatik |
| Dewey Decimal Classification: | 000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik |
| Open Access: | Open Access |
| Licence (German): |  Creative Commons - Namensnennung, Nicht kommerziell, Keine Bearbeitung |
