About this document
Lesson 4 - ROC Curve by fr.tortorella is a document available to read on EtoBox.
The document discusses performance assessment in two-class problems using the ROC curve, focusing on decision thresholds, Bayes criteria, and the evaluation of classifiers. It highlights the importance of measuring accuracy for each class separately, especially in unbalanced datasets, and introduces key metrics like True Positive Rate (TPR) and False Positive Rate (FPR). The ROC curve is presented as a tool for comparing classifiers and determining optimal operating points based on cost and prior probabilit
- Author
- fr.tortorella
- Language
- EN