Validation

One of the primary challenges in time series forecasting is the inherent uncertainty and variability over time, making it crucial to validate the accuracy and reliability of the models employed. TimeGPT offers the possibility for cross-validation and historical forecasts to help you validate your predictions.

What You Will Learn

1. Cross-Validation

   • Learn how to perform time series cross-validation across different continuous windows of your data.

2. Historical Forecasts

   • Generate in-sample forecasts to validate how TimeGPT would have performed in the past, providing insights into the model’s accuracy.