Runmin Wei authored a software package for evaluating multi-class classification models. The package computes areas under ROC and PR curves using micro-averaging and macro-averaging methods. Its methodology references academic papers by Van Asch (2013) and Pedregosa et al. (2011).
Use Cases
- Evaluate multi-class model performance based on ROC curve calculation
- Compare classifier performance across classes based on macro-averaging
- Visualize trade-offs between precision and recall based on PR curve generation
- Benchmark classification algorithms using micro-averaging methodology
Strengths
- Provides tools for both ROC and PR curve calculation, covering two common evaluation metrics
- Implements both micro-averaging and macro-averaging methods for multi-class scenarios
- Methodology is documented with references to specific academic papers
Limitations
- Column-level documentation is absent; field semantics must be inferred after download
- Row count is unknown, which may limit suitability assessment
- Last update date is unknown; freshness unverified
Provenance
- Source
- Runmin Wei
- Collection Method
- Software package development