# ROC and AUC

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**ROC Curve** Is the plot of Sensitivity/TPR (Y axis) vs (1-Specificity)/FPR (X axis). It is a graphical plot that illustrates the diagnostic ability of a binary classifier, as its **discrimination threshold is varied**. 
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AUC is a metric for how well a model fit the data (1 being absolutely perfect fit).
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![](/files/-M3tRRwFchB_WKbIGBXH)

{% embed url="<https://www.youtube.com/watch?v=OAl6eAyP-yo>" %}


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