a b/conf/experiment/data_dimensionality_sensitivity.yaml 

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# Configuration file for the data dimensionality sensitivity experiment





  
  

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# ==============================================================================





  
  

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# Defaults





  
  

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defaults:





  
  

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  - _self_





  
  

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  # Simulation settings





  
  

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  - /simulator: t_simulator #ty_simulator





  
  

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  # Model parametrization





  
  

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  - /models@EconML_CausalForestDML: EconML_CausalForestDML





  
  

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  - /models@EconML_DML: EconML_DML





  
  

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  - /models@EconML_DMLOrthoForest: EconML_DMLOrthoForest





  
  

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  - /models@EconML_DRLearner: EconML_DRLearner





  
  

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  - /models@EconML_DROrthoForest: EconML_DROrthoForest





  
  

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  - /models@EconML_ForestDRLearner: EconML_ForestDRLearner





  
  

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  - /models@EconML_LinearDML: EconML_LinearDML





  
  

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  - /models@EconML_LinearDRLearner: EconML_LinearDRLearner





  
  

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  - /models@EconML_SparseLinearDML: EconML_SparseLinearDML





  
  

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  - /models@EconML_SparseLinearDRLearner: EconML_SparseLinearDRLearner #EconML_SparseLinearDRLearner





  
  

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  - /models@EconML_SLearner_Lasso: EconML_SLearner_Lasso





  
  

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  - /models@EconML_TLearner_Lasso: EconML_TLearner_Lasso





  
  

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  - /models@EconML_XLearner_Lasso: EconML_XLearner_Lasso





  
  

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  - /models@Torch_SLearner: Torch_SLearner





  
  

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  - /models@Torch_TLearner: Torch_TLearner





  
  

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  - /models@Torch_XLearner: Torch_XLearner





  
  

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  - /models@Torch_DRLearner: Torch_DRLearner





  
  

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  - /models@Torch_RLearner: Torch_RLearner





  
  

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  - /models@Torch_TARNet: Torch_TARNet





  
  

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  - /models@Torch_DragonNet: Torch_DragonNet





  
  

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  - /models@Torch_DragonNet_2: Torch_DragonNet_2





  
  

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  - /models@Torch_DragonNet_4: Torch_DragonNet_4





  
  

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  - /models@Torch_ULearner: Torch_ULearner





  
  

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  - /models@Torch_RALearner: Torch_RALearner





  
  

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  - /models@Torch_PWLearner: Torch_PWLearner





  
  

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  - /models@Torch_FlexTENet: Torch_FlexTENet





  
  

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  - /models@Torch_CRFNet_0_01: Torch_CRFNet_0_01





  
  

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  - /models@Torch_CRFNet_0_001: Torch_CRFNet_0_001





  
  

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  - /models@Torch_CRFNet_0_0001: Torch_CRFNet_0_0001





  
  

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  - /models@Torch_ActionNet: Torch_ActionNet





  
  

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  - /models@DiffPOLearner: DiffPOLearner





  
  

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# EXPERIMENT AND DATA





  
  

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# ==============================================================================





  
  

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experiment_name: "data_dimensionality_sensitivity"





  
  

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# ==============================================================================





  
  

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# EXPERIMENTAL KNOB





  
  

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# ==============================================================================





  
  

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# Cohort sizes to be tested





  
  

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data_dims: [500, 1000, 1500, 2000, 2500, 3000] #[1000, 4000, 7000, 11000, 15000, 18000] #[25,32,40,47,55]





  
  

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compare_axis: "propensity" # "num_important_features"





  
  

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sim_propensity_type: "none_pred"





  
  

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sim_alpha: 1





  
  

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propensity_scales: [0, 2, 100]





  
  

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sample_sizes: [0.5, 1] # [0.3,0.6,0.9]





  
  

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n_samples: null





  
  

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important_feature_nums: [5, 10] # [5, 10, 15, 20, 25, 30, 35, 40, 45, 50]





  
  

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# ==============================================================================





  
  

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