Deterministic and Heuristic


Deterministic Models in Machine Learning typically refer to models where, given a specific input, the output is always the same. This determinism arises from the model's structure and the fixed set of rules it follows. Supervised Learning models, especially those dealing with labeled data, often exhibit deterministic behavior. For instance:


Heuristic Models, on the other hand, often involve elements of randomness or approximation. Unsupervised learning, working with unlabeled data, might lean towards heuristic approaches. For example: