What are some examples of interpretable models in AI?

What are some examples of interpretable models in AI?

Interpretable models in AI include decision trees, linear regression, and rule-based systems. They allow users to understand how decisions are made.

Can you explain why interpretability is important?

Interpretability is crucial for trust, accountability, and compliance, especially in fields like healthcare and finance.

How do decision trees work as an interpretable model?

Decision trees split data into branches based on feature values, making it easy to visualize and understand decision paths.

Are there any limitations to using interpretable models?

Yes, interpretable models may not capture complex patterns as well as black-box models like deep learning, leading to potential accuracy trade-offs.