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Computing precision and recall

The sklearn.metrics submodule has many functions that allow you to easily calculate interesting metrics. So far, you've calculated precision and recall by hand - this is important while you develop your intuition for both these metrics.

In practice, once you do, you can leverage the precision_score and recall_score functions that automatically compute precision and recall, respectively. Both work similarly to other functions in sklearn.metrics - they accept 2 arguments: the first is the actual labels (y_test), and the second is the predicted labels (y_pred).

Let's now try a training size of 90%.

Instrukcje 1/3

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  • Import precision_score from sklearn.metrics.