Articles by nzumel

Estimating Uncertainty of Utility Curves

October 9, 2020 | nzumel

Recently, we showed how to use utility estimates to pick good classifier thresholds. In that article, we used model performance on an evaluation set, combined with estimates of rewards and penalties for correct and incorrect classifications, to find a threshold that optimized model utility. In this article, we will show […]
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Squeezing the Most Utility from Your Models

October 5, 2020 | nzumel

In a previous article we discussed why it’s a good idea to prefer probability models to “hard” classification models, and why you should delay setting “hard” classification rules as long as possible. But decisions have to be made, and eventually you will have to set that threshold. How do ...
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Unrolling the ROC

August 17, 2020 | nzumel

In our data science teaching, we present the ROC plot (and the area under the curve of the plot, or AUC) as a useful tool for evaluating score-based classifier models, as well as for comparing multiple such models. The ROC is informative and useful, but it’s also perhaps overly ...
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