Lemke, C. and Gabrys, B., 2008. On the Benefit of Using Time Series Features for Choosing a Forecasting Method. In: 2nd European Symposium on Time Series Prediction, 17-19 Sep 2008, Porvoo, Finland.
Full text available as:
|PDF - Accepted Version|
In research of time series forecasting, a lot of uncertainty is still related to the question of which forecasting method to use in which situation. One thing is obvious: There is no single method that performs best on all time series. This work examines whether features extracted from time series can be exploited for a better understanding of different behaviour of forecasting algorithms. An extensive pool of automatically computable features is identified, which is submitted to feature selection algorithms. Finally, a possible relationship between these features and the performance of forecasting and forecast combination methods for the particular series is investigated.
|Item Type:||Conference or Workshop Item (Paper)|
|Subjects:||Generalities > Computer Science and Informatics > Artificial Intelligence|
Generalities > Computer Science and Informatics
|Group:||School of Design, Engineering & Computing > Smart Technology Research Centre|
|Deposited By:||INVALID USER|
|Deposited On:||19 Dec 2008 19:33|
|Last Modified:||07 Mar 2013 15:02|
Document DownloadsMore statistics for this item...
|Repository Staff Only -|
|BU Staff Only -|
|Help Guide -||Editing Your Items in BURO|