When should I use pruning in my algorithms?

What is pruning in algorithms?

Pruning is a technique used to reduce the size of search space in algorithms, especially in decision trees and search algorithms.

When should I consider using pruning?

You should consider using pruning when your algorithm is facing a large search space, which can lead to inefficiencies.

Can you give me an example of pruning in action?

Sure! In a decision tree, pruning can remove branches that have little importance, improving the model's performance.

Are there any downsides to using pruning?

Yes, if done excessively, pruning can lead to underfitting, where the model becomes too simple to capture the underlying patterns.