Summary

In this chapter, we investigated predicting events using machine learning by using R. We formatted a dataset into an R time series. We used a few methods to extract the constituent parts of the time series into trend, seasonal, and irregular components. We used different smoothing methods on the time series to arrive at a model. We used different mechanisms to forecast the time series based on the models.

In the next chapter, we will discuss supervised and unsupervised learning.