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+# Configuration file for the predictive scale sensitivity experiment
+# Also compares the nonlinearity of mechanisms
+# ==============================================================================
+
+# 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_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: "predictive_scale_sensitivity"
+# ==============================================================================
+
+# EXPERIMENTAL KNOB
+# ==============================================================================
+# Cohort sizes to be tested
+predictive_scales: [1e-3, 1e-1, 0.5, 2] #[1e-3, 1e-2, 1e-1, 0.5, 1, 2] #, 1.0]
+nonlinearity_scales: [0,1] #, 1] # If too unbalanced, the model may give an error because of there being too few instances for a certain class
+# ==============================================================================
+
+