Gradient Boosted Trees
- class omlt.gbt.gbt_formulation.GBTBigMFormulation(gbt_model)[source]
Bases:
omlt.formulation._PyomoFormulation- property input_indexes
Return the indices corresponding to the inputs of the ML model. This is a list of entries (which may be tuples for higher dimensional inputs).
- property output_indexes
Return the indices corresponding to the outputs of the ML model. This is a list of entries (which may be tuples for higher dimensional outputs).
- omlt.gbt.gbt_formulation.add_formulation_to_block(block, model_definition, input_vars, output_vars)[source]
References
Misic, V. “Optimization of tree ensembles.” Operations Research 68.5 (2020): 1605-1624.
Mistry, M., et al. “Mixed-integer convex nonlinear optimization with gradient-boosted trees embedded.” INFORMS Journal on Computing (2020).
- class omlt.gbt.model.GradientBoostedTreeModel(onnx_model, scaling_object=None, scaled_input_bounds=None)[source]
Bases:
object- property n_inputs
- property n_outputs
- property onnx_model
- property scaled_input_bounds
Return a list of tuples containing lower and upper bounds of neural network inputs
- property scaling_object
Return an instance of the scaling object that supports the ScalingInterface