What are the applications of AUC-ROC in machine learning?

What are the applications of AUC-ROC in machine learning?

AUC-ROC is widely used for evaluating the performance of classification models, especially in binary classification.

Can you explain what AUC and ROC stand for?

Sure! AUC stands for Area Under the Curve, and ROC stands for Receiver Operating Characteristic.

How does AUC-ROC help in model selection?

AUC-ROC helps compare different models by providing a single metric that summarizes their performance across all classification thresholds.

Are there specific industries that benefit from AUC-ROC?

Yes, industries like healthcare, finance, and marketing use AUC-ROC to assess models for disease prediction, fraud detection, and customer segmentation.