Recent Releases of fseval
fseval - 3.1.0
What's Changed
- Recipe/running on aws by @dunnkers in https://github.com/dunnkers/fseval/pull/86
- Install Node.js in the Devcontainer by @dunnkers in https://github.com/dunnkers/fseval/pull/87
- Updated schematic according to paper by @dunnkers in https://github.com/dunnkers/fseval/pull/88
- Add Developer instructions by @dunnkers in https://github.com/dunnkers/fseval/pull/89
- Add big feature selector benchmark by @dunnkers in https://github.com/dunnkers/fseval/pull/90
- Add statement of need to docs by @dunnkers in https://github.com/dunnkers/fseval/pull/92
Full Changelog: https://github.com/dunnkers/fseval/compare/v3.0.4...3.1.0
Scientific Software - Peer-reviewed
- Python
Published by dunnkers over 3 years ago
fseval - 3.0.4
What's Changed
- Fix license badge by @dunnkers in https://github.com/dunnkers/fseval/pull/80
- Improve installation instructions by @dunnkers in https://github.com/dunnkers/fseval/pull/81
- Add some docs explaining how to "analyze FS algorithm stability" by @dunnkers in https://github.com/dunnkers/fseval/pull/83
- Small-fix-in-algorithm-stability-plus-upgrade-docusaurus by @dunnkers in https://github.com/dunnkers/fseval/pull/84
Full Changelog: https://github.com/dunnkers/fseval/compare/v3.0.3...v3.0.4
Scientific Software - Peer-reviewed
- Python
Published by dunnkers over 3 years ago
fseval - 3.0.0
New release! 🚀
Many parts of the API changed for the sake of better documentation. Most importantly: - [x] Usage is now not primarily through a CLI, but by defining your own Hydra app. This lets the user easier understand what's going on. - [x] Classifiers/Regressors are now defined in separate configs. This makes the entire config easier to read/reason about. - [x] Docstrings for every configuration needed. - [x] Documentation website with Docusaurus. - [x] Much higher test coverage. Badges for test coverage and supported Python versions.
Checkout the new documentation website!
Scientific Software - Peer-reviewed
- Python
Published by dunnkers over 4 years ago
fseval - 2.1.0
Many fixes and new features. - [x] 🏷 More built-ins: add 5 OpenML datasets and add Infinite Selection (b52e0dad3b45172a9a63de76e426a22505938df4 and 008f9eda8a3f51e06fe29b77ed6f411130b367ec) - [x] 💪🏻 Add multiprocessing support (53987d079244eb2604f9b4ecd76ae28ec9080dd2, cacc902881bc92bde16d72863d2ede0d51774e5f) - [x] 🌺 Feature support and feature rankings are now also scored (9ee15a55809df235a7b152f34be8e35cf3916216) - [x] 📊 Upload raw feature ranker matrices, so they can be processed on the frontend (146bc47a23d11f3de7aad55dc795b0568d415adf) - [x] 🔨 Fix caching. Now behaves like expected. (07e631d56db3bfd666f519f2816a1db6930f8ec8, 86f4ca3b552bd50c0883fb5349bb6c49ede6e3d1) - [x] ⚙️ Upgrade to Hydra 1.1.0 (8e0d976ebb4dd70143578a4621745e68e14c9688) - [x] 📊 Feature support vectors are now validated in a separate step. Outputs another validation score. (dea00ab947c5b1a8816efd3c619d4512420d5637) - [x] 📊 Add charts as part of pipeline. This allows users to get interpretable results without any configuring on their part. (f050a87cbce8a2f614c4bcabc0ee2f5f72e6cb52)
Scientific Software - Peer-reviewed
- Python
Published by dunnkers almost 5 years ago
fseval - 2.0.3
- [x] Add FeatBoost support
- [x] Add Stability Selection support (forward-compatibility via fork)
Scientific Software - Peer-reviewed
- Python
Published by dunnkers about 5 years ago
fseval - 2.0.0 🚀
Completely rewritten framework, integrating wandb, hydra and sklearn for easily configurable and flexible feature selection benchmarking.
- [x] Beautifully visualize benchmarking results inside a wandb dashboard ✨✨
- [x] Ability to enqueue jobs in a Redis database using Hydra's RQ Launcher.
- [x] Both classification and regression datasets supported.
- [x] Multi-label classification and multi-output classification- and regression all supported.
- [x] Flexible dataset loading using adapters: adapters for OpenML and wandb artifacts are included.
- [x] Ability to dynamically define a feature importances ground-truth on any dataset - can be used to evaluate feature rankings.
- [x] Sophisticated evaluation metrics are used to evaluate the quality of a feature ranking.
🙌🏻
Scientific Software - Peer-reviewed
- Python
Published by dunnkers about 5 years ago
fseval - 1.0.0: Initial release
- [x] Benchmark feature selection algorithms
- [x] Complete pipeline for benchmarking: reading datasets, performing feature selection, computing evaluation metrics, plotting results
- [x] Written from the ground up to be parallel-compatible
- [x] SLURM interoperability (e.g. University of Groningen's Peregrine cluster)
- [x] CLI tool for submitting jobs
Scientific Software - Peer-reviewed
- Python
Published by dunnkers over 5 years ago