Fig. 1. Overview of the different domains and the process of supervised learning.

The left side represents the different domains of supervised learning going from artificial intelligence to machine learning and finally deep learning. The right side depicts the process of supervised learning. At the top right corner, the requirements for a good training data set are listed. The data is used for automated feature extraction, leading to the generation of a model, the performance of which is evaluated by its capability to correctly predict the labels of unseen instances (= test data). Based on the evaluation outcome, the model is retrained to refine the selected features and to optimize the model. After several rounds of retraining the final model emerges. AI artificial intelligence, DL deep learning, ML machine learning.