Java: Data Science Made Easy

Supervised learning

As we discussed previously, for supervised learning we have some information attached to each data point, the label, and we can train a model to use it and to learn from it. For example, if we want to build a model that tells us whether there is a dog or a cat on a picture, then the picture is the data point and the information whether it is a dog or a cat is the label. Another example is predicting the price of a house--the description of a house is the data point, and the price is the label. 

We can group the algorithms of supervised learning into classification and regression algorithms based on the nature of this information.

In classification problems, the labels come from some fixed finite set of classes, such as ...