HERA
HERA is a MATLAB based scientific ranking framework for paired benchmarking. It provides a hierarchical-compensatory logic, advanced effect-size statistics, and automated reporting capabilities.
For more information please refer to the Readme and Project Documentation.
What's New in v1.4.3?
This update introduces new domain-specific datasets (Examples 3 and 4) to demonstrate HERA's versatility, along with documentation updates and a configuration bug fix.
⚙️ Enhancements & New Datasets
- Benchmarking Datasets: Added new clinical (derived from OpenML Cardiovascular Disease) and weather (derived from WeatherAUS) datasets (Examples 3 & 4) to showcase HERA's versatility across diverse scientific domains.
- Documentation updates: Added instructions for reproducing results, added convergence troubleshooting advice, documented
selected_permutationsconfiguration parameters, and refined Python integration documentation.
🐛 Bug Fixes
- Bootstrap Configuration Override: Fixed a bug where manual bootstrap settings (
manual_B_thr,manual_B_ci, andmanual_B_rank) were overridden by defaults, by adding them to the dynamic configuration list.
Recent Major Features (from v1.4.0)
✨ Convergence Analysis Enhancements:
- New Scenario: Added a "Sensitivity" scenario with small effect sizes.
- JSON Configuration: All scenarios are fully customizable through a JSON configuration file
(For a full list of features, see the v1.4.0 Release Notes)
🖥️ Platform Support
- MATLAB Toolbox & Python Package: Windows, macOS (Intel & Apple Silicon), Linux
- Standalone Runtime Application: macOS (Apple Silicon ONLY)
📦 Compatibility
- MATLAB: Compatible with R2020a and newer.
- Python: Compatible with Python 3.9 through 3.12 and Matlab Runtime R2025b (25.2).
Full Changelog: v1.4.2...v1.4.3