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Gurobi Machine Learning Manual

Gurobi Machine Learning Manual

Contents

  • User Guide
    • Introduction
    • Usage Example
    • Supported Regression models
    • Mixed Integer Formulations
    • Further Reading
    • Bibliography
  • Examples
    • Surrogate Models
    • Student Enrollment
    • Adversarial Machine Learning
    • Price Optimization
  • API
    • add_predictor_constr
    • column_transformer
      • add_column_transformer_constr
      • ColumnTransformerConstr
    • decision_tree_regressor
      • add_decision_tree_regressor_constr
      • DecisionTreeRegressorConstr
    • gradient_boosting_regressor
      • add_gradient_boosting_regressor_constr
      • GradientBoostingRegressorConstr
    • linear_regression
      • add_linear_regression_constr
      • LinearRegressionConstr
    • logistic_regression
      • add_logistic_regression_constr
      • LogisticRegressionConstr
    • mlpregressor
      • add_mlp_regressor_constr
      • MLPRegressorConstr
    • pipeline
      • add_pipeline_constr
      • PipelineConstr
    • pls_regression
      • add_pls_regression_constr
      • PLSRegressionConstr
    • random_forest_regressor
      • add_random_forest_regressor_constr
      • RandomForestRegressorConstr
    • preprocessing
      • add_polynomial_features_constr
      • add_standard_scaler_constr
      • sklearn_transformers
      • PolynomialFeaturesConstr
      • StandardScalerConstr
    • keras
      • add_keras_constr
      • KerasNetworkConstr
    • sequential
      • add_sequential_constr
      • SequentialConstr
    • xgboost_regressor
      • add_xgboost_regressor_constr
      • add_xgbregressor_constr
      • XGBoostRegressorConstr
    • lgbm_regressor
      • add_lgbm_booster_constr
      • add_lgbmregressor_constr
      • LGBMConstr
    • Internal APIs
      • base_predictor_constr
        • AbstractPredictorConstr
      • neural_net
        • BaseNNConstr
      • layers
        • AbstractNNLayer
        • ActivationLayer
        • DenseLayer
      • activations
        • Identity
        • ReLU
      • decision_tree_model
        • AbstractTreeEstimator
      • skgetter
        • SKgetter
        • SKtransformer
      • base_regressions
        • BaseSKlearnRegressionConstr
  • Contact Us
  • License
  • gurobi.com ressources

Links

  • gurobi.com
  • docs.gurobi.com
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random_forest_regressorΒΆ

Module for formulating a sklearn.ensemble.RandomForestRegressor into a Model.

Functions

add_random_forest_regressor_constr(gp_model, ...)

Formulate random_forest_regressor in gp_model.

Classes

RandomForestRegressorConstr(gp_model, ...)

Class to formulate a trained sklearn.ensemble.RandomForestRegressor in a gurobipy model.

Next
add_random_forest_regressor_constr
Previous
PLSRegressionConstr
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