[6ac965]: / conf / experiment / expertise_sensitivity.yaml

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# Configuration file for the propensity sensitivity experiment
# Also compares the unbalancedness of the treatment assignment
# ==============================================================================
# Defaults
defaults:
- _self_
# Simulation settings
- /simulator: ty_simulator
# Model parametrization
- /models@EconML_CausalForestDML: EconML_CausalForestDML
- /models@EconML_DML: EconML_DML
- /models@EconML_DMLOrthoForest: EconML_DMLOrthoForest
- /models@EconML_DRLearner: EconML_DRLearner
- /models@EconML_DROrthoForest: EconML_DROrthoForest
- /models@EconML_ForestDRLearner: EconML_ForestDRLearner
- /models@EconML_LinearDML: EconML_LinearDML
- /models@EconML_LinearDRLearner: EconML_LinearDRLearner
- /models@EconML_SparseLinearDML: EconML_SparseLinearDML
- /models@EconML_SparseLinearDRLearner: EconML_SparseLinearDRLearner #EconML_SparseLinearDRLearner
- /models@EconML_SLearner_Lasso: EconML_SLearner_Lasso
- /models@EconML_TLearner_Lasso: EconML_TLearner_Lasso
- /models@EconML_XLearner_Lasso: EconML_XLearner_Lasso
- /models@Torch_SLearner: Torch_SLearner
- /models@Torch_TLearner: Torch_TLearner
- /models@Torch_XLearner: Torch_XLearner
- /models@Torch_DRLearner: Torch_DRLearner
- /models@Torch_RLearner: Torch_RLearner
- /models@Torch_TARNet: Torch_TARNet
- /models@Torch_DragonNet: Torch_DragonNet
- /models@Torch_DragonNet_2: Torch_DragonNet_2
- /models@Torch_DragonNet_4: Torch_DragonNet_4
- /models@Torch_ULearner: Torch_ULearner
- /models@Torch_RALearner: Torch_RALearner
- /models@Torch_PWLearner: Torch_PWLearner
- /models@Torch_FlexTENet: Torch_FlexTENet
- /models@Torch_CRFNet_0_01: Torch_CRFNet_0_01
- /models@Torch_CRFNet_0_001: Torch_CRFNet_0_001
- /models@Torch_CRFNet_0_0001: Torch_CRFNet_0_0001
- /models@Torch_ActionNet: Torch_ActionNet
- /models@DiffPOLearner: DiffPOLearner
# EXPERIMENT AND DATA
# ==============================================================================
experiment_name: "expertise_sensitivity"
# ==============================================================================
# EXPERIMENTAL KNOB
# ==============================================================================
# Cohort sizes to be tested
alphas: [0,0.125,0.25,0.375,0.5,0.625,0.75,0.875,1]
#alphas: [0,0.5, 1]
propensity_types: ["prog_tre", "none_prog", "none_tre", "none_pred"] #"prog_pred",
# alphas: [1]
n_samples: null
# propensity_types: ["prog_pred"] #,"none_pred","none_prog"]
# ==============================================================================