In Chapter 9, Forecasting with Linear Regression, we saw how a basic regression model could utilize some simple steps to create a robust time series forecast. The use of a linear regression model for time series forecasting can be easily generalized to other regression approaches, in particular, machine learning-based regressions. In this chapter, we will focus on the use of machine learning models for time series forecasting using the h2o package. This chapter requires some basic knowledge of the training and tuning process of machine learning models.
In this chapter, we will cover the following topics:
- Introduction to the h2o package and its functionality
- Feature engineering of time series data
- Forecasting with the Random Forest model
- Forecasting with the gradient boosting machine learning model
- Forecasting with the automate machine...
