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AUC (Area Under the Curve): Difference between revisions
Created page with "==Introduction== In machine learning, the AUC (Area Under the ROC Curve) is a popular metric used to evaluate the performance of binary classification models. It measures the ability of the model to distinguish between the positive and negative classes based on the output probabilities of the model. ==What is AUC?== AUC is a measure of the area under the curve of a Receiver Operating Characteristic (ROC) curve, which is a graph that represents the trade-off between the..."
(Created page with "==Introduction== In machine learning, the AUC (Area Under the ROC Curve) is a popular metric used to evaluate the performance of binary classification models. It measures the ability of the model to distinguish between the positive and negative classes based on the output probabilities of the model. ==What is AUC?== AUC is a measure of the area under the curve of a Receiver Operating Characteristic (ROC) curve, which is a graph that represents the trade-off between the...") |
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