What are some effective evaluation methods for AI models?

What are some effective evaluation methods for AI models?

Some effective evaluation methods include cross-validation, confusion matrix, and ROC-AUC analysis.

Can you explain how cross-validation works?

Cross-validation involves partitioning the data into subsets, training the model on some subsets, and validating it on others.

What is a confusion matrix?

A confusion matrix is a table used to evaluate the performance of a classification model by comparing predicted and actual values.

How do I interpret the ROC-AUC score?

The ROC-AUC score measures the model's ability to distinguish between classes; a score of 1 indicates perfect classification.