Added a method to increase the interpretability of interactions. Updated the documentation.

Added a method, calculate_local_contribution_from_selected_terms, to increase the interpretability of interactions (also works for main effects). Updated the documentation.

Made it possible to increase interpretability by explicitly reducing the number of terms

Provided an option to increase interpretability at the expense of predictiveness by setting the max_terms hyperparameter. See the API references for more information.

Added more functionality to tweak models

Now it is possible to optionally provide the following for each predictor:

• Learning rate.
• Penalty for non-linearity.
• Penalty for interactions.

Speeded up the algorithm in special cases

• Speeded up the algorithm when penalty_for_non_linearity=1.0 or penalty_for_interactions=1.0.
• Automatically rounding penalty_for_non_linearity and penalty_for_interactions to the nearest boundary in the [0.0, 1.0] range if the user specifies something outside of this range.

Controlling interpretability

Added two constructor parameters to help controlling the interpretability versus predictiveness trade-off:

• penalty_for_non_linearity (default = 0.0). Specifies a penalty in the range [0.0, 1.0] on terms that are not linear effects. A higher value increases model interpretability but can hurt predictiveness.
• penalty_for_interactions (default = 0.0). Specifies a penalty in the range [0.0, 1.0] on interaction terms. A higher value increases model interpretability but can hurt predictiveness.

Linear effects

Added the possibility to use linear effects only for a custom number of initial boosting steps. This can be used for example to increase interpretability by building models that place more weight on linear effects.

Minor bugfix

Fixed a minor bug that sometimes added unnecessary terms to the model.

Fix of minor inconsistency

Fixed a minor (and for practical purposes insignificant) inconsistency w.r.t. rounding errors.

Bugfix

Fixed a bug that caused less interaction terms than intended to be considered for model inclusion.

Reverted a default parameter and updated the documentation

Reverted the default learning rate for APLRClassifier to 0.1.
Updated the documentation.