Ensemble Learning for Time Series Prediction

By Abdelhamid Bouchachia. 2008

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Dongjin Song
2. Yao Qin
3. Haifeng Chen
4. Wei Cheng
5. Guofei Jiang
6. Shun-Yao Shih
7. Garrison W. Cottrell
8. Hung-yi Lee

Citations in the corpus

• A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction (2017, methodology): “, 2008], ensemble methods [Bouchachia and Bouchachia, 2008], and Gaussian processes [Frigola and Rasmussen, 2014], the drawback is that most of these approaches employ a predefined nonlinear form and may not be able to capture the true underlying nonlinear relationship appropriately.”
• Temporal pattern attention for multivariate time series forecasting (2018, methodology): “For that reason, substantial effort has been made for non-linear models for time series forecasting based on kernel methods (Chen, Wang, and Harris 2008), ensembles (Bouchachia and Bouchachia 2008), or Gaussian processes (Frigola and Rasmussen 2014).”