How accurate are decision forests in machine learning?

How accurate are decision forests in machine learning?

Decision forests, like random forests, are generally very accurate due to their ensemble nature, averaging multiple decision trees.

What factors affect their accuracy?

Factors include the number of trees, depth of trees, feature selection, and the quality of the training data.

Can you give an example of their accuracy in a real-world application?

Sure! In medical diagnosis, decision forests have shown over 90% accuracy in predicting diseases based on patient data.

How do they compare to other algorithms?

They often outperform single decision trees and can be more robust than algorithms like logistic regression, especially with complex data.