Evaluation Study of Linear Combination Technique for SVM related Time Series Forecasting
- Xian Cheng, School of Economics & Management, Southwest Jiaotong University, ChengDu, SiChuan, China
- Ji Wu, School of Business, Sun Yat-sen University, GuangZhou, China
- Jin Xu, School of Economics & Management, Southwest Jiaotong University, Chengdu, Sichuan, China
AbstractTime series forecasting and SVM are widely used in many domains, for example, smart city and digital services. Focusing on SVM related time series forecasting model, in this paper we empirical investigate the performance of eight linear combination techniques by using M3 competition dataset which includes 3003 time series. The results reveals that the “forecast combination puzzle” is not exist for combining SVM related forecasting model as the simple average is almost the worst combination technique.
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