Interactive Explanation of ROC AUC Score

A binary classification is a machine learning model that classifies input data into two classes. We need different metrics to train or evaluate the performance of ML models. The Area Under the Receiver Operating Characteristic Curve (ROC AUC) score is a popular metric for evaluating binary classification models. In this post, we will try to understand the intuition behind the ROC AUC with simple and interactive visualizations.

The post is located in my personal page https://maitbayev.github.io/posts/roc-auc/

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