Galaxy-ml

New Features

- Extend binarize target scorers to support stacking estimators, i.e., use binarize target estimator as meta estimator.
- Adds `cv_results` attributes to `estimator_attributes` tool.
- Adds loading prefitted model for prediction in `keras_model_builder` tool.
- Adds `save_weights` and `load_weights` for keras classifier/regressor models.
- Merges keras model builder

Changes

- Refactors the multiple scoring input for searchcv and simplify cv_results output.
- Refactors import system, get rid of exec import.

Bug Fixes

- Fixes stacking estimators whitelist issue and other import issues.
- Fixes bases typo error in stacking ensembles tool
- Fixes multiple scoring error in train_test_split mode

New Features

- Adds `StackingCVClassifier`, `StackingClassifier` and `StackingRegressor` to `Stacking_ensembles` tool, and makes explicit base estimator and meta estimator building options.
- Adds `.gitattributes` and `.gitignore`.

Changes

- Changes `extended_ensemble_ml.xml` to `stacking_ensembles.xml`.
- Moves src to subfolder `Galaxy-ML`

Bug Fixes

- Fix safepickler classobj issue

New Features

- Makes `RepeatedOrderedKFold`.
- Makes `train_test_split` tool and adds `train_test_split` to searchcv tool.
- Adds `jpickle` to persist sklearn objects.
- Makes `TDMScaler`.
- Makes search parameter `options` in `search_model_validation` tool using `from_dataset`, the `get_params` output of
`estimator_attributes` tool.
- Restructures `estimator_attributes` tool to be workflow friendly.

Changes

- Separate `OrderedKFold` into `model_validations` module.
- Refactors `SafePickler` class and pickle white list loading system for better CPU and Memory efficiency.
- Separates `feature_selector` module out from `utils`.

Bug Fixes

- Fix safepickler classobj issue

New Features

- SearchCV tool selects param from `get_params()` dataset.
- Adds `extended_ensemble_ml` tool which wraps `StackingCVRegressor` to ensemble machine learning.
- Extends `estimator_attributes` tool to output `get_params()`.
- Adds support of multipleprocessing in `IRAPSCore`.

Changes

- Removes the limit of `n_jobs=1` for `IRAPSClassifier`
- Changes named estimators in `pipeline_builder` tool. Use `make_pipeline` instead of `Pipeline` initiation.


Bug Fixes

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