v0.1.12

What's Changed

• Update MODNet citations by @ml-evs in #59
• add new database for fast featurization by @ppdebreuck in #65
• Rebalance classif by @ppdebreuck in #64
• feature selection updates by @ppdebreuck in #58
• Fit genetic by @gregheymans in #50
• AUC as val metric by @ppdebreuck in #68
• new database + multi-label classification by @ppdebreuck in #70
• num_neurons supposed to be a list with 4 entries (?) by @sgbaird in #75
• Integrity test on saved model by @ppdebreuck in #85
• composition state example (hardness + load), dataset, and citation by @sgbaird in #76

New Contributors

• @dependabot made their first contribution in #54
• @gregheymans made their first contribution in #50
• @sgbaird made their first contribution in #75

Full Changelog: v0.1.11...v0.1.12

v0.1.11

What's Changed

• pass classification to kfold split by @ppdebreuck in #55
• A minor fix when running with increasing batch_size scheme by @ml-evs in #57

Full Changelog: v0.1.10...v0.1.11

v0.1.10

What's Changed

• README: add docs badge and move up docs section by @ml-evs in #40
• Adjust ext_data tests to not depickle large MODData by @ml-evs in #43
• Fix benchmark arguments when performing HP optimisation by @ml-evs in #41
• Probabilistic models, fine-grained parallelization for training and feature selection, and smarter data cleaning by @ppdebreuck in #44
• Docs fixes, Add black auto-formatting, linting and pre-commit to CI by @ml-evs in #48
• Post process + classification bug by @ppdebreuck in #53

Full Changelog: v0.1.9...v0.1.10

v0.1.9

What's Changed

• v0.1.9 updates from latest preprint: parallel hyperparameter optimisation, nested CV, matbench benchmarking code by @ppdebreuck in #23
• Update README by @ml-evs in #29
• Fix a couple of problems by @ml-evs in #30
• Fix for specifying inner CV fold number by @ml-evs in #31
• fix train-val split when no CV is chosen in fit_preset by @ppdebreuck in #33
• Update tutorials by @ppdebreuck in #35
• Initial docs generation by @ppdebreuck in #32

Full Changelog: v0.1.8...v0.1.9

v0.1.8

What's Changed

• Automated validation procedure for hyper parameters by @ppdebreuck in #18
• Refactoring feature selection by @ml-evs in #19
• Refactoring of MODNetModel by @ml-evs in #16
• Tweaking dependencies by @ml-evs in #21
• Classification implementation by @ppdebreuck in #20
• Add ability to load precomputed cross NMI from figshare by @ml-evs in #22

Full Changelog: v0.1.7...v0.1.8

v0.1.7

What's Changed

• Refactored featurization into new module with presets by @ml-evs in #15

Full Changelog: 0.1.6...v0.1.7

v0.1.6

refactor changes

v0.1.5: Fixed various bugs,

- Make target names and material_ids more flexible by including any iterable
- Fixed target construction issue in MODNet, now expects a list or (n_materials,n_target) nd array
- Fixed evaluation of dataframes in if constructions
- Removed mpids attribute
- Fixed feature_selection .loc error
It is now possible to pass any Iterable for target names and material ids.

v0.1.2

zero-range-features bug fix

v0.1.1

Added large files (db and moddatas)