5. Classification

Classification consists in associating each piece of data with a class, the classes corresponding in our case to the activities. The algorithm used for classification is called a classifier. There are two types of classification:

• supervised classification: a data set with a known class is available. This data set is used to build the classifier model, which is then used to determine the class of new data;

• unsupervised classification: the class of no data is known at the outset. The aim is to find a distribution that groups individuals into classes. This is done in such a way as to create classes that are as homogeneous and distinct from one another as possible.