What are the disadvantages of decision trees?

What are the disadvantages of decision trees?

Decision trees can be prone to overfitting, especially with complex datasets. They can also be unstable with small changes in data.

Can you explain overfitting in more detail?

Overfitting occurs when a model learns the noise in the training data instead of the actual pattern, leading to poor performance on unseen data.

Are there any other limitations of decision trees?

Yes, decision trees can be biased towards features with more levels and may not perform well with imbalanced datasets.

What are some alternatives to decision trees?

Alternatives include ensemble methods like random forests, gradient boosting, and other algorithms like support vector machines.