What is post-training evaluation in AI?
An example of an AI chatbot conversation about post-training evaluation in AI systems.
What is post-training evaluation in AI?
Post-training evaluation is the process of assessing an AI model's performance after it has been trained.
Why is it important to evaluate AI models after training?
It's crucial to ensure the model meets performance standards and generalizes well to new data.
What metrics are commonly used in post-training evaluation?
Common metrics include accuracy, precision, recall, F1 score, and AUC-ROC, depending on the task.
How can I improve my model's performance based on evaluation results?
You can improve performance by tuning hyperparameters, using more data, or trying different algorithms.
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