A hyperparameter is a configuration value set before an algorithm begins learning. It guides the training process, distinct from model parameters learned from data, and greatly influences a model's final performance.
A hyperparameter is a configuration value set before an algorithm begins learning. It guides the training process, distinct from model parameters learned from data, and greatly influences a model's final performance.