ROCR is a package designed for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It offers over 25 performance measures that can be combined to create two-dimensional performance curves, including ROC graphs, precision/recall plots, lift charts, and cost curves. ROCR integrates seamlessly with R's graphics capabilities, allowing for highly adjustable plots. The package is easy to use, requiring only three commands and reasonable default values for optional parameters. It is available under the GNU General Public License and is platform-independent. ROCR is particularly useful for pattern classification tasks in bioinformatics, where class skew, misclassification costs, and experimental noise are common challenges. The package provides a comprehensive suite for evaluating and visualizing classifier performance, making it a valuable tool for researchers in biomedical data analysis.ROCR is a package designed for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It offers over 25 performance measures that can be combined to create two-dimensional performance curves, including ROC graphs, precision/recall plots, lift charts, and cost curves. ROCR integrates seamlessly with R's graphics capabilities, allowing for highly adjustable plots. The package is easy to use, requiring only three commands and reasonable default values for optional parameters. It is available under the GNU General Public License and is platform-independent. ROCR is particularly useful for pattern classification tasks in bioinformatics, where class skew, misclassification costs, and experimental noise are common challenges. The package provides a comprehensive suite for evaluating and visualizing classifier performance, making it a valuable tool for researchers in biomedical data analysis.