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mlu-explain committed Mar 18, 2022
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<h1 class='body-header'>The Tradeoff... Again</h1>
<p class='body-text'>
To wrap everything up, let's look again at our cancer dataset again, this time from the lens of the tradeoff between the four different evaluation metrics
we've discussed: <span class='bold'>accuracy</span>, <span class='bold'>precision</span>, <span class='bold'>recall</span>, and the <span class='bold'>f1-score</span>.
we've discussed: <span class='bold'>accuracy</span>, <span class='bold'>precision</span>, <span class='bold'>recall</span>, and the <span class='bold'>F1-score</span>.
To view this tradeoff explicitly, we'll plot each metric's score as a function of our classification threshold:
</p>
<br>
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