ConceptIntermediate
What is the main idea behind the Fredf model for time series forecasting?
The main idea behind FreDF is to forecast directly in the frequency domain rather than relying solely on conventional temporal objectives. It addresses the bias caused by label autocorrelation in standard mean squared error losses by using a frequency-domain learning objective that decorrelates labels, yielding a statistically sound and empirically superior approach for multi-step forecasting.
Key points
- FreDF stands for Frequency enhanced Direct Forecasting framework.
- It targets bias in conventional temporal mean squared error objectives caused by label autocorrelation.
- It introduces a frequency-domain learning objective that decorrelates the labels.
- The approach provides a statistically sound and empirically superior alternative for multi-step forecasting.
Source:AI for Time Series_ Volume 1_ Unlocking Patterns with Deep Learning· Fredf: Learning to Forecast in the Frequency Domain· p. 15–17
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AI for Time Series_ Volume 1_ Unlocking Patterns with Deep Learning
Min Wu;Emadeldeen Eldele;Zhenghua Chen;Shirui Pan;Qingsong Wen;Xiaoli Li;
First edition · CRC Press