111 monthly time series, including the 11 from the reduced set.
Includes a wide range of real-world business patterns (e.g., industry data), making it a robust test for model generalization.
The "masked" nature of the data (anonymized origin) ensures that models must rely on time series patterns rather than domain-specific knowledge. Practical Considerations
The series vary in length (68 to 144 observations) and include seasonal, non-seasonal, and "difficult" patterns with outliers and structural breaks. Key Strengths
A review of typically refers to the dataset from the NN3 Forecasting Competition (2006–2007), a seminal event in neural networks and computational intelligence for time series forecasting. This file usually contains a collection of 111 monthly time series drawn from empirical business data. Dataset Overview
Contestants were traditionally required to forecast 18 points into the future.
