How to Make Baseline Predictions for Time Series Forecasting with Python

Last Updated on August 21, 2019

Establishing a baseline is essential on any time series forecasting problem.

A baseline in performance gives you an idea of how well all other models will actually perform on your problem.

In this tutorial, you will discover how to develop a persistence forecast that you can use to calculate a baseline level of performance on a time series dataset with Python.

After completing this tutorial, you will know:

• The importance of calculating a baseline of performance on time series forecast problems.
• How to develop a persistence model from scratch in Python.
• How to evaluate the forecast from a persistence model and use it to establish a baseline in performance.

Kick-start your project with my new book Time Series Forecasting With Python, including step-by-step tutorials and the Python source code files for all examples.

Let’s get started.

• Updated Apr/2019: Updated the link to dataset.