What are the common challenges in AI model evaluation?

What are the common challenges in AI model evaluation?

Some common challenges include data quality, overfitting, and lack of interpretability.

Can you explain how data quality affects model evaluation?

Data quality impacts model evaluation by influencing accuracy; poor data can lead to misleading results.

What is overfitting and how can it be avoided?

Overfitting occurs when a model learns noise instead of the signal. It can be avoided using techniques like cross-validation.

Why is interpretability important in AI models?

Interpretability is crucial as it helps stakeholders understand model decisions, ensuring trust and compliance.