Understanding the ROC-AUC Curve

<p><strong><em>In binary classification, the threshold is indeed a pivotal aspect.&nbsp;</em></strong>When you&rsquo;re predicting the probability of an instance belonging to a particular class, a threshold determines at what probability you classify an instance as the positive class (1) or the negative class (0).</p> <p>Imagine your email service has a spam filter that uses a classification model to decide whether an incoming email is spam or not. The model computes a score (probability) for each email, representing the likelihood it&rsquo;s spam.</p> <p><a href="https://medium.com/@msong507/understanding-the-roc-auc-curve-cc204f0b3441"><strong>Click Here</strong></a></p>