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Deciding on a primary metric

As you have seen, several metrics can be useful to evaluate the performance of classification models, including accuracy, precision, recall, and F1-score.

In this exercise, you will be provided with three different classification problems, and your task is to select the problem where precision is best suited as the primary metric.

This exercise is part of the course

Supervised Learning with scikit-learn

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