update

feature_importance/01_ablation_classification_script.sh

@@ -5,6 +5,7 @@
 
 source activate mdi
 # Need to specify --result_name --ablate_features(default all features) --fitted(default not fitted)
-command="01_run_ablation_classification.py --nreps 1 --config mdi_local.real_data_classification --split_seed ${1} --ignore_cache --create_rmd --ablate_features 20 --result_name Juvenile --fitted True"
+command="01_run_ablation_classification.py --nreps 1 --config mdi_local.real_data_classification --split_seed ${1} --ignore_cache --create_rmd --folder_name diabetes_classification_final --fit_model True --positive_masking True --absolute_masking True --negative_masking True"
+
 # Execute the command
 python $command

feature_importance/01_ablation_regression_script.sh

@@ -5,7 +5,7 @@
 
 source activate mdi
 # Need to specify --result_name --ablate_features(default all features) --fitted(default not fitted)
-command="01_run_ablation_regression.py --nreps 1 --config mdi_local.real_data_regression --split_seed ${1} --ignore_cache --create_rmd --ablate_features 20 --result_name CCLE_2000"
+command="01_run_ablation_regression.py --nreps 1 --config mdi_local.real_data_regression --split_seed ${1} --ignore_cache --create_rmd --folder_name diabetes_final --fit_model True --positive_masking True --absolute_masking True --negative_masking True"
 
 # Execute the command
 python $command

feature_importance/01_ablation_regression_script_synthetic.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+#SBATCH [email protected]
+#SBATCH --mail-type=ALL
+#SBATCH --partition=yugroup
+
+source activate mdi
+# Need to specify --result_name --ablate_features(default all features) --fitted(default not fitted)
+command="01_run_ablation_regression.py --nreps 1 --config mdi_local.synthetic_data_linear --split_seed 0 --simulation_seed ${1} --ignore_cache --create_rmd --folder_name linear_synthetic --fit_model True --positive_masking True --absolute_masking True --negative_masking True"
+
+# Execute the command
+python $command

feature_importance/01_ablation_script_class.sh

@@ -5,5 +5,5 @@ slurm_script="01_ablation_classification_script.sh"
 for rep in {1..10}
 do
     sbatch $slurm_script $rep  # Submit SLURM job using the specified script
-    sleep 10
+    sleep 2
 done

feature_importance/01_ablation_script_regr.sh

@@ -1,9 +1,9 @@
 #!/bin/bash
 
-slurm_script="01_ablation_regression_script.sh"
+slurm_script="01_ablation_regression_script_synthetic.sh"
 
 for rep in {1..10}
 do
     sbatch $slurm_script $rep  # Submit SLURM job using the specified script
-    sleep 5
+    sleep 2
 done

feature_importance/01_auroc_regression_script_linear.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+#SBATCH [email protected]
+#SBATCH --mail-type=ALL
+#SBATCH --partition=yugroup
+
+source activate mdi
+# Need to specify --result_name --ablate_features(default all features) --fitted(default not fitted)
+command="01_run_auroc_synthetic.py --nreps 1 --config mdi_local.synthetic_data_linear --split_seed 0 --simulation_seed ${1} --ignore_cache --create_rmd --folder_name linear_synthetic_new --fit_model True"
+
+# Execute the command
+python $command

feature_importance/01_auroc_regression_script_lss.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+#SBATCH [email protected]
+#SBATCH --mail-type=ALL
+#SBATCH --partition=yugroup
+
+source activate mdi
+# Need to specify --result_name --ablate_features(default all features) --fitted(default not fitted)
+command="01_run_auroc_synthetic.py --nreps 1 --config mdi_local.synthetic_data_lss --split_seed ${1} --ignore_cache --create_rmd --folder_name lss_synthetic --fit_model True"
+
+# Execute the command
+python $command

feature_importance/01_auroc_regression_script_poly.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+#SBATCH [email protected]
+#SBATCH --mail-type=ALL
+#SBATCH --partition=yugroup
+
+source activate mdi
+# Need to specify --result_name --ablate_features(default all features) --fitted(default not fitted)
+command="01_run_auroc_synthetic.py --nreps 1 --config mdi_local.synthetic_data_poly --split_seed ${1} --ignore_cache --create_rmd --folder_name poly_synthetic --fit_model True"
+
+# Execute the command
+python $command

feature_importance/01_auroc_script_regr.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+
+slurm_script="01_auroc_regression_script_linear.sh"
+
+for rep in {1..3}
+do
+    sbatch $slurm_script $rep  # Submit SLURM job using the specified script
+    sleep 2
+done