How do we evaluate the performance of AI models?

How do we evaluate the performance of AI models?

Evaluating AI models typically involves metrics like accuracy, precision, recall, and F1 score. What specific model are you interested in?

I'm looking at a classification model for image recognition.

For image recognition, you might focus on accuracy and confusion matrices. Have you already collected some test data?

Yes, I have a dataset ready. How should I split it?

A common approach is to split your dataset into training, validation, and test sets, often in a 70-20-10 ratio. Would you like to know more about each set's purpose?

Yes, please explain the purpose of each set.

The training set is used to train the model, the validation set helps tune hyperparameters, and the test set evaluates final performance.