diff --git a/scripts/ml/ml_iterator.py b/scripts/ml/ml_iterator.py
index 8ebb88c..7ea16fb 100755
--- a/scripts/ml/ml_iterator.py
+++ b/scripts/ml/ml_iterator.py
@@ -24,6 +24,14 @@ from MultClfs import *
 from GetMLData import *
 from SplitTTS import *
 
+skf_cv = StratifiedKFold(n_splits = 10
+                          #, shuffle = False, random_state= None)
+                           , shuffle = True,**rs)
+
+#rskf_cv = RepeatedStratifiedKFold(n_splits = 10
+#                                  , n_repeats = 3
+#                                  , **rs)
+
 # param dict for getmldata()
 gene_model_paramD = {'data_combined_model'       : False
                     , 'use_or'                   : False
@@ -89,14 +97,21 @@ for gene, drug in ml_gene_drugD.items():
             mmDD = {}
             for k, v in paramD.items():
                 scoresD = MultModelsCl(**paramD[k]
-                                    , tts_split_type = split_type
                                     , sel_cv = skf_cv
-                                    , blind_test_df =  tempD['X_bts']
-                                    , blind_test_target = tempD['y_bts']
-                                    , scale_numeric = ['min_max']
+                                    , tts_split_type = split_type
+
                                     , add_cm = True 
                                     , add_yn = True
-                                    , return_formatted_output = True)
+                                    
+                                    , scale_numeric = ['min_max']
+                                    
+                                    , run_blind_test = True
+                                    , blind_test_df =  tempD['X_bts']
+                                    , blind_test_target = tempD['y_bts']
+                                    , return_formatted_output = True
+                                    , random_state = 42
+                                    , n_jobs = os.cpu_count()                                   
+                                    )
                 mmDD[k] = scoresD
 
             # Extracting the dfs from within the dict and concatenating to output as one df