Figure 1.

Supervised, unsupervised, and reinforcement learning. Machine learning tasks are categorized into supervised, unsupervised, or reinforcement learning. Supervised learning is used for prediction (classification or regression), whereas unsupervised learning aims to reveal hidden patterns in data. Reinforcement learning is another way of learning where an algorithm learns the best action based on its consequences, and is well suited for game theory and control theory. However, it has not had a significant role in clinical research because it requires simulating many “wrong actions” to learn. *Dimensionality reduction can also be performed in a supervised manner.