Pruning

Pruning is the process of trimming or removing parts of a model, like a decision tree or neural network, to improve efficiency and performance. In machine learning, this means eliminating unnecessary or less important elements to reduce complexity, which can help the model run faster, use less memory, and sometimes increase accuracy by preventing overfitting. Think of it as tidying up a cluttered workspace—by removing redundant pieces, the task becomes more streamlined and effective.