Which type of ML algorithm will meet these requirements?
Supervised learning
Unsupervised learning
Semi-supervised learning
Reinforcement learning
Explanations:
Supervised learning requires labeled data with known outcomes, but financial trading involves sequential decisions based on uncertain future rewards.
Unsupervised learning deals with finding hidden patterns in data without predefined labels, which is not suitable for sequential decision-making in trading.
Semi-supervised learning uses both labeled and unlabeled data but is not designed for decision-making in dynamic, reward-driven environments like trading.
Reinforcement learning is well-suited for environments where agents make decisions, receive feedback (rewards), and learn from interactions, like in trading.