Chapter 9: Introducing Data Frame Analytics

In the first section of this book, we took an in-depth tour of anomaly detection, the first machine learning capability to be directly integrated into the Elastic Stack. In this chapter and the following one, we will take a dive into the new machine learning features integrated into the stack. These include outlier detection, a novel unsupervised learning technique for detecting unusual data points in non-timeseries indices, as well as two supervised learning features, classification and regression.

Supervised learning algorithms use labeled datasets – for example, a dataset describing various aspects of tissue samples along with whether or not the tissue is malignant – to learn a model. This model can then be used to make predictions on previously unseen data points (or tissue samples, to continue our example). When the target of prediction is a discrete variable or a category such as a malignant or non-malignant tissue...