Releases: ISG-Siegen/Auto-Surprise
Releases · ISG-Siegen/Auto-Surprise
v0.1.9
What's Changed
- fix: numpy.random.RandomState is no longer an accepted random state b… by @thededlier in #50
- update setup configs by @thededlier in #51
- Update build configs by @thededlier in #52
Full Changelog: v0.1.8...v0.1.9
Auto-Surprise v0.1.8
tl;dr Updated dependencies and cleaned up required libraries
What's Changed
- Bump urllib3 from 1.25.9 to 1.26.5 by @dependabot in #41
- Bump babel from 2.8.0 to 2.9.1 by @dependabot in #42
- Create workflow for tests by @thededlier in #44
- Cleanup requirements and create v2 config for docs by @thededlier in #45
- Bump version by @thededlier in #46
Full Changelog: 0.1.7...v0.1.8
Auto-Surprise v0.1.7
- Rename continuous_parallel strategy to it's correct name - SMBO
- Early stop if baseline loss not reached after a set number of iterations
- Bot security version updates
Auto-Surprise v0.1.6
- Can now set random seed to reproduce experiment results
- Updated requirements to have
rich
- Updated documentation to include benchmark results
Auto-Surprise v0.1.5
- Conditionally define similarity options space. This allows for more precise hyper parameter tuning as the number of parameters are reduced in some configurations.
- Pretty print results table
- Attach trials to the final result. This could be used in the future to allow for early stopping.
Auto-Surprise v0.1.4 - Minor Feature Update
- Ability for user to select which algorithms to be optimized with the
algorithms
argument ofEngine
- Replaced
debug
option ofEngine
withverbose
. This also controls verbosity for Surprise and Hyperopt
Auto-Surprise v0.1.3 - Bug Fixes
v0.1.2 had a breaking bug that swapped the values given for time_limit with max_evals. If you are using v0.1.2 please update to this version. Sorry for any inconvenience.
Auto-Surprise v0.1.2 - Minor Updates
- Updated logging: better logging of results of each iteration for each algorithm.
Auto-Surprise v0.1.1
- BaselineOnly now also has baseline options for hyperparameter optimisation
- Default cross validation iterations changed to 5
- Fix results for non parameterised algorithm results not logged
Initial Release
Initial release which allows for automated algorithm selection and hyper-parameter tuning.