Machine Learning with Swift

Supervised learning

Supervised learning is arguably the most common and easy-to-understand type of ML . All supervised learning algorithms have one prerequisite in common: you should have a labeled dataset to train them. Here, a dataset is a set of samples, plus an expected output (label) for each sample. These labels play the role of supervisor during the training.

In different publications, you'll see different synonyms for labels, including dependent variable, predicted variable, and explained variable.

The goal of supervised learning is to get a function that for every given input returns a desired output. In the most simplified version, a supervised learning process consists of two phases: training and inference. During the first phase, ...