Multi-Objective Model Selection for Time Series Forecasting

Understand

Research on time series forecasting has predominantly focused on developing methods that improve accuracy.

• However, other criteria such as training time or latency are critical in many real-world applications.
• We therefore address the question of how to choose an appropriate forecasting model for a given dataset among the plethora of available forecasting methods when accuracy is only one of many criteria.
• For this, our contributions are two-fold.