lets see if this goes through

Author: zachrewolinski

feature_importance/feature_ranking.sh

@@ -3,7 +3,7 @@
 #SBATCH --mail-type=ALL
 
 source activate mdi
-command="ranking_importance_local_sims.py --nreps 1 --config mdi_local.real_x_sim_y.diabetes-regression.linear-model --split_seed ${1} --ignore_cache --create_rmd --result_name diabetes-reg-linear"
+command="ranking_importance_local_sims.py --nreps 1 --config mdi_local.real_x_sim_y.diabetes-regression.linear-model --split_seed 1 --ignore_cache --create_rmd --result_name diabetes-reg-linear"
 
 # Execute the command
 python $command

feature_importance/fi_config/mdi_local/real_x_sim_y/diabetes-regression/linear-model/dgp.py

@@ -7,7 +7,8 @@
 X_PARAMS_DICT = {
     "source": "imodels",
     "data_name": "diabetes_regr",
-    "sample_row_n": None
+    "sample_row_n": 400
+    #"sample_row_n": None
 }
 
 Y_DGP = linear_model
@@ -25,5 +26,4 @@
 #                                     "300": 300, "400": 400}}
 
 VARY_PARAM_NAME = ["heritability"]
-VARY_PARAM_VALS = {"heritability": {"0.1": 0.1, "0.2": 0.2,
-                                    "0.4": 0.4, "0.8": 0.8}}
+VARY_PARAM_VALS = {"heritability": {"0.4": 0.4, "0.8": 0.8}}

feature_importance/fi_config/mdi_local/real_x_sim_y/diabetes-regression/linear-model/models.py

@@ -7,7 +7,7 @@
 
 ESTIMATORS = [
     [ModelConfig('RF', RandomForestRegressor, model_type='tree',
-                other_params={'n_estimators': 100, 'min_samples_leaf': 1, 'max_features': 0.33, 'random_state': 42})]
+                other_params={'n_estimators': 100, 'min_samples_leaf': 5, 'max_features': 0.33, 'random_state': 42})]
 ]
 
 FI_ESTIMATORS = [