prcbench

prcbench evaluates classifier performance on imbalanced datasets using precision-recall curves to provide more informative assessment than ROC plots.

Key Features:

• Precision-Recall Plot Calculation: Fast and accurate computation of precision-recall curves for assessing classifier performance on imbalanced classes.
• Efficiency Under Various Conditions: Engineered to perform efficiently and robustly across different dataset conditions.
• Comprehensive Functionalities: Includes multiple functions for detailed performance evaluation of classifiers beyond basic curve calculation.

Scientific Applications:

• Bioinformatics and imbalanced-data analysis: Applied to assess classifier performance in bioinformatics and other domains where class imbalance is prevalent.
• Model selection and validation: Aids in accurate assessment of classifiers to inform model selection and validation processes.

Methodology:

Computes precision-recall curves for classifier evaluation and is implemented in R with C++ to combine R statistical routines with C++ computational efficiency.