Which metric would you use to evaluate a model's performance in a multi-class cl

Which metric would you use to evaluate a model's performance in a multi-class classification problem?

Which metric would you use to evaluate a model's performance in a multi-class classification problem?

Step 1: Understand that a multi-class classification problem involves more than two classes (categories) to predict.
Step 2: Learn about the F1 score, which is a measure that combines precision and recall to evaluate a model's performance.
Step 3: Recognize that in a multi-class setting, you can calculate the F1 score for each individual class.
Step 4: Calculate the F1 score for each class separately, which gives you a score for how well the model performs on that class.
Step 5: Average the F1 scores of all classes to get the Macro F1 Score, which treats all classes equally.

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