What's Changed
The main update of this release is to use the new nonlinear capabilities in Gurobi 11 for modeling
the logistic regression. Namely, if the user has Gurobi 11, the attribute
[FuncNonLinear](https://www.gurobi.com/documentation/current/refman/funcnonlinear.html#attr:FuncNonlinear) is set for
the nonlinear constraints with the logistic function created by the package.
In our tests this results in better results (smaller errors in the solution and sometimes faster).
The corresponding parts of the documentation have been updated. In particular the
[Student admission example](https://gurobi-machinelearning.readthedocs.io/en/latest/auto_examples/example2_student_admission.html#sphx-glr-auto-examples-example2-student-admission-py)
uses this and there is no more discussion on tuning the piecewise-linear approximation.
Other smaller updates regard the documentation that has been reorganized. In particular with the goal of documenting
better the internal objects that the package constructs and uses.
* Test with both gurobi 10.0.3 and 11.0.0 by twbraam in https://github.com/Gurobi/gurobi-machinelearning/pull/241
* Updates for Gurobi 11 by pobonomo in https://github.com/Gurobi/gurobi-machinelearning/pull/240
* Accept list of lists of variables as input to add predictor function by pobonomo in https://github.com/Gurobi/gurobi-machinelearning/pull/247
* Restructure and enhance documentation by pobonomo in https://github.com/Gurobi/gurobi-machinelearning/pull/256
**Full Changelog**: https://github.com/Gurobi/gurobi-machinelearning/compare/v1.3.3...v1.4.0