Data structures
Work in progress...
Main.OCTHaGOn.GlobalModel — TypeContains all constraints and data to solve the global optimization optimization problem. Add linear constraints to a GlobalModel through JuMP.@constraint(gm.model, ...), and nonlinear constraints using add_nonlinear_constraint.
Main.OCTHaGOn.BlackBoxLearner — TypeUnion of BlackBoxClassifier and BlackBoxRegressor types.
Main.OCTHaGOn.BlackBoxClassifier — TypeAllows for approximation of constraints using OCTs. Can be added to GlobalModel using add_nonlinear_constraint or add_nonlinear_or_compatible.
Main.OCTHaGOn.BlackBoxRegressor — TypeAllows for approximation of continuous functions or objectives using ORTs. Can be added to GlobalModel using add_nonlinear_constraint or add_nonlinear_or_compatible.
Main.OCTHaGOn.LinkedLearner — TypeUnion of LinkedClassifier and LinkedRegressor.
Main.OCTHaGOn.LinkedClassifier — TypeContains data for a constraint that is repeated. Add to GlobalModel using add_linked_constraint.
Main.OCTHaGOn.LinkedRegressor — TypeContains data for a constraint that is repeated. Add to GlobalModel using add_linked_constraint.