LGBMConstr#

class gurobi_ml.lightgbm.lgbm_regressor.LGBMConstr(gp_model, lgbm_regressor, input_vars, output_vars, epsilon=0.0, **kwargs)#

Class to model trained lightgbm.Booster in a gurobipy model.

Stores the changes to gurobipy model for formulating the predictor.

Attributes:

Methods

`get_error`([eps])	Returns error in Gurobi's solution with respect to prediction from input.
`print_stats`([abbrev, file])	Print statistics on model additions stored by this class.
`remove`()	Remove from gp_model everything that was added to embed predictor.

get_error(eps=None)#

Returns error in Gurobi’s solution with respect to prediction from input.

Returns:: error – Assuming that we have a solution for the input and output variables x, y. Returns the absolute value of the differences between predictor.predict(x) and y. Where predictor is the regression model represented by this object.
Return type:: ndarray of same shape as gurobi_ml.modeling.base_predictor_constr.AbstractPredictorConstr.output
Raises:: NoSolution – If the Gurobi model has no solution (either was not optimized or is infeasible).

print_stats(abbrev=False, file=None)#

Print statistics on model additions stored by this class.

This function prints detailed statistics on the variables and constraints that where added to the model.

Includes a summary of the estimators that it contains.

Parameters:: file (None, optional) – Text stream to which output should be redirected. By default sys.stdout.

remove()#: Remove from gp_model everything that was added to embed predictor.

property default_name#: Default base name base used for automatic name generation.

property input#

Input variables of embedded predictor.

property input_values#

Values for the input variables if a solution is known.

Returns:: output_value
Return type:: ndarray or pandas dataframe with values
Raises:: NoSolution – If the Gurobi model has no solution (either was not optimized or is infeasible).

property output#

Output variables of embedded predictor.

property output_values#

Values for the output variables if a solution is known.

Returns:: output_value
Return type:: ndarray or pandas dataframe with values
Raises:: NoSolution – If the Gurobi model has no solution (either was not optimized or is infeasible).