In machine learning paradigms, if the training of the statistical model is performed on data which labelled, which is to say that each piece of training input is provided with the corresponding correct output, the training process is referred to as supervised learning. In contrast, unsupervised learning, the statistical model exclusively learns from unlabelled data.