A Naive Prediction of the Future: Building Baseline Forecasting Models with Simplicity and Insight

Forecasting the future may sound like a mystical art, but in the realm of data science, it often starts with simple, straightforward models that serve as the foundation for more complex techniques. In this article, we explore the concept of naive forecasting by building several baseline models. We will delve into:

• Defining a Baseline Model
• Setting a Baseline Using the Mean
• Building a Baseline Using the Mean of the Previous Window of Time
• Creating a Baseline Using the Previous Timestep
• Implementing the Naive Seasonal Forecast

This comprehensive guide is designed for anyone who wants to understand the fundamentals of time series forecasting through simple, interpretable models. Whether you are a beginner or a seasoned data scientist looking for a refresher on baseline methods, this article provides detailed explanations, practical examples, diagrams, and source code — all crafted uniquely for your learning experience.

Table of Contents

1. Introduction
2. Defining a Baseline Model
3. Setting a Baseline Using the Mean