Final results for matbench submission, including results on the larger `matbench_perovskites`, `matbench_mp_gap`, `matbench_mp_is_metal`, `matbench_mp_eform` tasks.
0.2.2
A fix to the published data that does not change the aggregate results. `KFold` and not `StratifiedKFold` was used for classification splits; as the datasets were balanced, this had a limited effect on the results.
0.2.1
Minor repository reorganisation relative to v0.2. Added an MIT license.
0.2
Results as reported in final paper at [10.1088/1361-648X/ac1280](https://doi.org/10.1088/1361-648X/ac1280).
NB: the MODNet version used was v0.1.10, and NOT v0.1.9 as reported in the `requirements.txt`.
0.2.0
What's Changed * Add new default feature preset and updates for new `matminer` & `pymatgen` versions by ml-evs in https://github.com/ppdebreuck/modnet/pull/101 * Bump tensorflow from 2.10.0 to 2.10.1 by dependabot in https://github.com/ppdebreuck/modnet/pull/112 * fix verbosity by ppdebreuck in https://github.com/ppdebreuck/modnet/pull/128 * Replace deprecated NumPy and Tensorflow calls by ml-evs in https://github.com/ppdebreuck/modnet/pull/123 * Add mode where each featurizer is applied individually by ml-evs in https://github.com/ppdebreuck/modnet/pull/127
What's Changed * Add pinned requirements file by ml-evs in https://github.com/ppdebreuck/modnet/pull/94 * Make sure new deps do not get overwritten by CI by ml-evs in https://github.com/ppdebreuck/modnet/pull/99 * Add instructions for installing pinned requirements and prepare release by ml-evs in https://github.com/ppdebreuck/modnet/pull/108