What are some real-world applications of decision trees?

What are some real-world applications of decision trees?

Decision trees are widely used in various fields such as finance for credit scoring, healthcare for diagnosis, and marketing for customer segmentation.

Can you explain how decision trees are used in healthcare?

In healthcare, decision trees help in diagnosing diseases by analyzing patient symptoms and medical history to suggest possible conditions.

What are the advantages of using decision trees?

Some advantages include their simplicity, interpretability, and ability to handle both numerical and categorical data.

Are there any limitations to decision trees?

Yes, decision trees can be prone to overfitting, especially with complex datasets, and they may not perform well with unbalanced data.

How do decision trees compare to other machine learning models?

Decision trees are easier to interpret than many models, but they may not be as accurate as ensemble methods like random forests.