Nn3.zip Apr 2026

The series vary in length (68 to 144 observations) and include seasonal, non-seasonal, and "difficult" patterns with outliers and structural breaks. Key Strengths

The NN3 competition was designed to evaluate how modern neural network (NN) and computational intelligence (CI) methods compare to traditional statistical benchmarks like those used in the M3 competition. Composition: nn3.zip

It is a standard historical benchmark in the forecasting community and is often included in modern research packages like the tscompdata R package on GitHub. The series vary in length (68 to 144

Contestants were traditionally required to forecast 18 points into the future. nn3.zip

The "masked" nature of the data (anonymized origin) ensures that models must rely on time series patterns rather than domain-specific knowledge. Practical Considerations