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The performance of a model can be evaluated by calculating the area under the curve (AUC). Can you tell me how you would go about calculating the AUC for a model?

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Anonymous

7 months ago

Yeah. AUC is calculated after calculating the sensitivity vs specificity plot which is know to be used for classification tasks. We want to calculate the classification stats for each threshold from 0 to 1 eg 0, 0.1 etc. Then we plot the TPR and FPR on the plot. Once we plot, we can calculate the area under curve (AUC). Higher the AUC better. It ranges between 0 and 1.

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Interview question asked to Machine Learning Engineers interviewing at Microsoft, Deliveroo, Duolingo and others: The performance of a model can be evaluated by calculating the area under the curve (AUC). Can you tell me how you would go about calculating the AUC for a model?.

The performance of a model can be evaluated by calculating the area under the curve (AUC). Can you tell me how you would go about calculating the AUC for a model?

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