add_pls_regression_constr

gurobi_ml.sklearn.pls_regression.add_pls_regression_constr(gp_model, pls_regression, input_vars, output_vars=None, **kwargs)

Formulate pls_regression in gp_model.

The formulation predicts the values of output_vars using input_vars according to pls_regression.

Parameters:

• gp_model (gurobipy model) – The gurobipy model where the predictor should be inserted.

• pls_regression (sklearn.cross_decomposition.PLSRegression) –

  The linear regression to insert. It can be of any of the following types:

  • sklearn.cross_decomposition.PLSRegression

  • sklearn.cross_decomposition.PLSCanonical

  input_vars: mvar_array_like

  Decision variables used as input for random forest in model.

  output_vars: mvar_array_like, optional

  Decision variables used as output for random forest in model.

Returns:

Object containing information about what was added to gp_model to formulate pls_regression.

Return type:

PLSRegressionConstr

Notes

See add_predictor_constr for acceptable values for input_vars and output_vars