Worc

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Fixed
~~~~~
- Bug where most recent added estimators were not valid in SimpleWORC.
- SelectorMixin is now imported directly from sklearn.feature_selection,
as sklearn.feature_selection.base is deprecated and will be removed.

Changed
~~~~~~~
- Apply variance threshold selection before feature scaling, otherwise
variance is always the same for all features.
- RELIEF, selection using a model, PCA, and univariate testing default
use changed from 0.20 to 0.275.

Added
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- Functionality in plotting images functions.
- Documentation on how to use your own features.

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Fixed
~~~~~
- SimpleWORC and BasicWORC now support multilabel workflows.
- SimpleWORC and BasicWORC now support use of masks.

Added
~~~~~~~
- Unit testing for multilabel workflows.

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Fixed
~~~~~
- Bug in flattening of plot_ranked_posteriors function.
- Bug in plot_images: could not handle 2D images when applying slicing.
- Bug in precision-recall curve.
- Bug in performance estimation plotting.
- Preflighcheck now also accepts labels from txt or XNAT.

Added
~~~~~~~
- Label file can now also be separated by semicolons.

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Fixed
~~~~~
- Bugfix when PCA cannot be fitted.
- Bugfix when using LOO cross-validation in performance evaluation.
- Fix XGboost verson, as newest version automatically uses multihreading,
which is unsuitable for clusters.
- Bug in decomposition for Evaluation.
- RankedPosteriors naming of images was rounded to an integer, now unrounded
- Several fixes for regression.
- Regression in unit test.
- Several fixes for using 2D images.

Changed
~~~~~~~
- Reverted back to weighted f1-score without predictproba for optimization,
more stable.
- Updated regressors in SimpleWORC.

Added
~~~~~~~
- Option to combine features from a varying number of objects per patient,
e.g. by averaging or taking the maximum.
- Logarithmic z-score scaler to be more robust to non-normal distributions
and outliers.
- Linear and Ridge regression.
- Precision-recall curves.

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Fixed
~~~~~
- MAJOR: Bug in SearchCV sorting of output files.
- Bug in StatisticalTest for Manhattan plot.
- Bug in evaluate when using a test set.
- Bug in SearchCV for fitting preprocessing.
- Fix random states in boosting estimators.

Changed
~~~~~~~
- IMPORTANT: previously, used f1_score based on estimator.predict function.
Now, use predict_proba.
- New defaults for random-search and ensemble.

Added
~~~~~~~
- All performances to output statistics.
- Script for plotting of errors in classification. Not embedded yet.
- Option to refit top performing workflows and save them.
- Part to conduct experiment with varying random search and ensemble sizes.

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Fixed
~~~~~
- Some function cleaning: removing redundant parts / variables.

Changed
~~~~~~~
- Part of developper documentation for addinf methods to hyperoptimization.
- Default config: SelectFromModel incorporated, so now also use
that in feature selection step.

Added
~~~~~~~
- OneHotEncoder to workflows / HyperOptimization.
- Documentation updates.
- SelectFromModel expanded and properly integrated in workflow.
- AdaBoost as classifier and regressor.
- XGDBoost as classifier and regressor.
- Plotting of hyperparameters of best workflows in Evaluate network.
- Plotting of p-values of features.