The ROC Curve and AUC Calculator is an interactive tool designed to evaluate the performance of binary classification models. The Receiver Operating Characteristic (ROC) curve plots the True Positive Rate (TPR) against the False Positive Rate (FPR) at various threshold levels, providing a visual representation of the model’s ability to distinguish between classes. The Area Under the Curve (AUC) quantifies the overall performance of the model, with higher values indicating better discrimination.

This tool allows users to input their model’s predictions and true labels, dynamically generating the ROC curve and calculating the AUC. It also provides a downloadable PDF report summarizing the results.

Key Features:

1. Interactive Input Fields : Users can upload or input their model’s predicted probabilities and true labels.
2. Dynamic Visualization : The tool generates the ROC curve in real-time using Chart.js.
3. AUC Calculation : The Area Under the Curve (AUC) is calculated and displayed alongside the ROC curve.
4. PDF Download : A fully functional PDF download button generates a professional report with the ROC curve, AUC value, and other relevant metrics.
5. Modern Design : The tool is colorful, stylish, and modern, ensuring a visually appealing user experience.
6. Self-Contained : The tool operates within its own container, ensuring no interference with the page header or footer.

Use Cases:

1. Model Evaluation : Data scientists can use this tool to assess the performance of their binary classification models.
2. Threshold Selection : Experiment with different thresholds to observe how they impact the ROC curve and AUC.
3. Educational Purposes : Students and educators can use this tool to understand the concept of ROC curves and AUC.
4. Business Analytics : Businesses can leverage this tool to evaluate predictive models for tasks like fraud detection, customer churn prediction, and medical diagnosis.

How It Works:

1. Input Data : Users input their model’s predicted probabilities and true labels.
2. Calculation : The tool processes the inputs to calculate the TPR, FPR, and AUC.
3. Visualization : Results are displayed in an interactive and visually appealing format, including the ROC curve and AUC value.
4. Download Report : Users can download a PDF report containing the ROC curve, AUC value, and other relevant metrics for further analysis.