Aplr

Latest version: v10.7.4

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6.1.0

Reverted to updating the intercept in each boosting step. The reason is slightly better predictiveness on several datasets.

6.0.0

- Deprecated the constructor field intercept in APLRRegressor.
- Bugfix related to the Python wrapper that previously did not pickle correctly.
- Bugfix related to a warning when the model has not been trained yet but is attempted used.

5.0.0

Changed intercept estimation methodology and consequently deprecated intercept_steps. The intercept is now fully estimated in the first boosting step.

4.1.0

Improved fitting when group_mse is used as a loss function. Fixed a minor bug related to handling of incorrect user input (an error is now thrown if m=0).

4.0.0

Added APLRClassifier, enabling two-class and multi-class classification. Also two small bugfixes in APLRRegressor and a renaming of the get_m() method to get_optimal_m().

3.1.0

Added the weibull loss function.

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