Release 0.12.1

0.12.1

• Dataset features can now be easily accessed with the property dataset.features
• model.test_estimators with CV will keep using CV if it's refitting the best estimator.
• Result now has a .parameters attribute to show what parameters generated the result
• Switch to pyproject.toml for project metadata
• Updated documentation to use california housing dataset instead of boston
• Updated documentation to remove deprecated parameters from estimators

Release v0.11.0

New functionality

• Added load_demo_dataset function

• If the dataset has no train set score_estimator will now run create_train_test with default configurations

• Model.make_prediction now takes a threshold argument when making a binary classification

• All ML-tooling logging messages now go to stdout instead of stderr

• Can pass a feature pipeline to Model which will then automatically generate a
  combined feature_pipeline + estimator Pipeline

• Can pass a feature pipeline to Dataset.plot methods, to apply preprocessing
  before visualization

• New config implementation. If you need to reset the configuration, you should use Model.config.reset_config()