Time Series Forecasting as Supervised Learning

Last Updated on August 15, 2020

Time series forecasting can be framed as a supervised learning problem.

This re-framing of your time series data allows you access to the suite of standard linear and nonlinear machine learning algorithms on your problem.

In this post, you will discover how you can re-frame your time series problem as a supervised learning problem for machine learning. After reading this post, you will know:

  • What supervised learning is and how it is the foundation for all predictive modeling machine learning algorithms.
  • The sliding window method for framing a time series dataset and how to use it.
  • How to use the sliding window for multivariate data and multi-step forecasting.

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.

Time Series Forecasting as Supervised Learning

Time Series Forecasting as Supervised Learning
Photo by Jeroen Looyé, some rights reserved.

Supervised Machine Learning

The majority of practical machine learning uses supervised learning.

Supervised learning is
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