Change Log

From v3.0.1 to v3.0.2

Fixes

Fixed a bug where an attached standardizer would be refit when calling
QSPRModel.predictMols with use_applicability_domain=True.
Fixed a bug with use_applicability_domain=True in QSPRModel.predictMols
where an error would be raised if there were invalid molecules in the input.
Fixed a bug where dataset type was not properly set to numeric
in MlChemADWrapper.contains
Fixed a bug in QSPRDataset where property transformations were not applied.
Fixed a bug where an attached standardizer would be refit when calling
QSPRModel.predictMols with use_applicability_domain=True.
Fixed random seed not set in FoldsFromDataSplit.iterFolds for ClusterSplit.
Fixed a bug where class ratios were shuffled in the RatioDistributionAlgorithm.

The module containing the sole model base class (QSPRModel) was renamed
from models to model.
Restrictions on numpy versions were removed to allow for more flexibility in
package installations. However, the BorutaFilter feature selection method does not
function with numpy versions 1.24.0 and above. Therefore, this functionality now
requires a downgrade to numpy version 1.23.0 or lower. This was reflected in the
documentation and numpy itself outputs a reasonable error message if the version is
incompatible.
Data type in MlChemADWrapper is now set to float64 by default, instead
of float32.
Saving of models after hyperparameter optimization was improved to ensure parameters
are always propagated to the underlying estimator as well.

The DataFrameDescriptorSet class was extended to allow more flexibility when joining
custom descriptor sets.
Added the prepMols method to DescriptorSet to allow separated customization of
molecule preparation before descriptor calculation.
The package can now be installed from the PyPI repository 🐍📦.
New argument (refit_optimal) was added to HyperparameterOptimization.optimize()
method to make refitting of the model with optimal parameters easier.

None.