Hey #machinelearning #fediverse, I'm having trouble understanding how AUC/ROC works. What I grasped so far was the true and false positive rates. I also understood that we use AUC/ROC to choose the most accurate model from a group. Is there any quick way to generate a ROC graph with two models? I'm looking at https://www.kaggle.com/code/akbarhuseynov23/roc-and-auc and also looking for a practice binary classification problem to build a ROC curve and choose a model based on it.
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