What's Changed * fixed bugged conditionals in evaluate() by kyledmiller in https://github.com/ppdebreuck/modnet/pull/210 * Add simple test for evaluate by ml-evs in https://github.com/ppdebreuck/modnet/pull/211
New Contributors * kyledmiller made their first contribution in https://github.com/ppdebreuck/modnet/pull/210
What's Changed * Deprecated `BayesianMODNetModel` and update deps by ml-evs in https://github.com/ppdebreuck/modnet/pull/182 * Fix issue with `fit_preset` invoking fit incorrectly during refit by ml-evs in https://github.com/ppdebreuck/modnet/pull/181 * 3.10 compatibility by ppdebreuck in https://github.com/ppdebreuck/modnet/pull/198 * Improve evaluate (custom loss, ...) by ppdebreuck in https://github.com/ppdebreuck/modnet/pull/194 * Drop Python 3.8 and update other deps by ml-evs in https://github.com/ppdebreuck/modnet/pull/201 * Bump matminer version by ml-evs in https://github.com/ppdebreuck/modnet/pull/199 * Attempt at bumping pymatgen and matminer by ml-evs in https://github.com/ppdebreuck/modnet/pull/203 * Backwards compatibility of test data with pymatgen by ml-evs in https://github.com/ppdebreuck/modnet/pull/206 * Properly handle Bayesian model import failure by ml-evs in https://github.com/ppdebreuck/modnet/pull/207
What's Changed * Fixed refit=0 in FitGenetic, it behaves as before (ensemble of 10 best architecture, ensembled over the `nested `(default 5) folds) * Bump pymatgen from 2023.1.30 to 2023.7.20, compatible with cython 3
0.4.0
Updated benchmarks using MODNet v0.1.12, using genetic algorithm hyperparameter optimization for all tasks.
0.3.1
Minor bug fixes to the way our workflow/scripts were disseminated, with no associated changes to the benchmark results.
0.3.0
Final results for matbench submission, including results on the larger `matbench_perovskites`, `matbench_mp_gap`, `matbench_mp_is_metal`, `matbench_mp_eform` tasks.