Nn3.zip [ Updated · WORKFLOW ]

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

Includes a wide range of real-world business patterns (e.g., industry data), making it a robust test for model generalization.

The series vary in length (68 to 144 observations) and include seasonal, non-seasonal, and "difficult" patterns with outliers and structural breaks. Key Strengths nn3.zip

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

For modern use, researchers often access these files through the NN3 Official Website or data science repositories like Kaggle . Critical Reception Key Strengths A review of typically refers to

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.

11 monthly time series used as a small-scale pilot. Critical Reception It is a standard historical benchmark

111 monthly time series, including the 11 from the reduced set.