Machine Learning Models for Time-Series
Machine learning has come a long way in recent years, and this is reflected in the methods available to time-series predictions. We've introduced a few state-of-the-art machine learning methods for time-series in Chapter 4, Introduction to Machine Learning for Time-Series. In the current chapter, we'll introduce several more machine learning methods.
We'll go through methods that are commonly used as baseline methods, or that stand out in terms of either performance, ease of use, or their applicability. I'll introduce k-nearest neighbors with dynamic time warping and gradient boosting for time-series as a baseline and we'll go over other methods, such as Silverkite and gradient boosting. Finally, we'll go through an applied exercise with some of these methods.
We're going to cover the following topics:
- More machine learning methods for time-series
- K-nearest neighbors with dynamic...
