Hands-On Ensemble Learning with Python

Supervised learning

In examples such as those in the previous section, the data consisted of some features and a target; no matter whether the target was quantitative (regression) or categorical (classification). Under these circumstances, we call the dataset a labeled dataset. When we try to produce a model from a labeled dataset in order to make predictions about unseen or future data (for example, to diagnose a new tumor case), we make use of supervised learning. In simple cases, supervised learning models can be visualized as a line. This line's purpose is to either separate the data based on the target (in classification) or to closely follow the data (in regression).

The following figure illustrates a simple regression example. Here, ...