Question: A. How are outputs typically evaluated in machine learning? 1. By their economic impact, such as financial gains or improvements in efficiency. 2. By technical

A. How are outputs typically evaluated in machine learning?

1. By their economic impact, such as financial gains or improvements in efficiency.

2. By technical performance metrics, such as accuracy, precision, recall, or F1 score.

3. By the amount of input data provided to the model.

4. By the time taken by the model to generate predictions.

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