Machine Learning with Swift

Using instance-based models for classification and clustering

Instance-based machine learning algorithms are usually easy to understand as they have some geometrical intuition behind them. They can be used to perform different kinds of tasks, including classification, regression, clustering, and anomaly detection.

It's easy to confuse classification and clustering at first. Just to remind you, classification is one of the many types of supervised learning. The task is to predict some discrete label from the set of features (Figure 3.4, left pane). Technically, classification goes in two types: binary (check yes or no), and multiclass (yes/no/maybe/I don't know/can you repeat the question?). But in practice, you can always build a multiclass ...