diff --git a/scripts/ml/ml_functions/MultClfs_logo_skf.py b/scripts/ml/ml_functions/MultClfs_logo_skf.py
index 1b4c2ff..e2fc932 100755
--- a/scripts/ml/ml_functions/MultClfs_logo_skf.py
+++ b/scripts/ml/ml_functions/MultClfs_logo_skf.py
@@ -261,34 +261,34 @@ def MultModelsCl_logo_skf(input_df
     #======================================================
     models = [('AdaBoost Classifier'            , AdaBoostClassifier(**rs) )
                , ('Bagging Classifier'          , BaggingClassifier(**rs, **njobs, bootstrap = True, oob_score = True, verbose = 3, n_estimators = 100) )
-               # , ('Decision Tree'             , DecisionTreeClassifier(**rs) ) 
-               # , ('Extra Tree'                , ExtraTreeClassifier(**rs) )
-               # , ('Extra Trees'               , ExtraTreesClassifier(**rs) ) 
-               # , ('Gradient Boosting'         , GradientBoostingClassifier(**rs) )
-               # , ('Gaussian NB'               , GaussianNB() )
-               # , ('Gaussian Process'          , GaussianProcessClassifier(**rs) )
-               # , ('K-Nearest Neighbors'       , KNeighborsClassifier() ) 
-               # , ('LDA'                       , LinearDiscriminantAnalysis() )
-               # , ('Logistic Regression'       , LogisticRegression(**rs) )
-               # , ('Logistic RegressionCV'     , LogisticRegressionCV(cv = 3, **rs))
-               # , ('MLP'                       , MLPClassifier(max_iter = 500, **rs) ) 
-               # , ('Multinomial'               , MultinomialNB() )
-               # , ('Naive Bayes'               , BernoulliNB() )
-               # , ('Passive Aggresive'         , PassiveAggressiveClassifier(**rs, **njobs) )
-               # , ('QDA'                       , QuadraticDiscriminantAnalysis() )
-               # , ('Random Forest'             , RandomForestClassifier(**rs, n_estimators = 1000, **njobs ) ) 
-               # , ('Random Forest2'            , RandomForestClassifier(min_samples_leaf = 5
-               #                                                         , n_estimators     = 1000
-               #                                                         , bootstrap        = True
-               #                                                         , oob_score        = True
-               #                                                         , **njobs
-               #                                                         , **rs
-               #                                                         , max_features     = 'auto') ) 
-               #  , ('Ridge Classifier'          , RidgeClassifier(**rs)  )
-               #  , ('Ridge ClassifierCV'        , RidgeClassifierCV(cv = 3) )          
-               #  , ('SVC'                       , SVC(**rs) ) 
-               #  , ('Stochastic GDescent'       , SGDClassifier(**rs, **njobs) )
-               #  , ('XGBoost'                   , XGBClassifier(**rs, verbosity = 0, use_label_encoder = False, **njobs) )
+               , ('Decision Tree'             , DecisionTreeClassifier(**rs) ) 
+               , ('Extra Tree'                , ExtraTreeClassifier(**rs) )
+               , ('Extra Trees'               , ExtraTreesClassifier(**rs) ) 
+               , ('Gradient Boosting'         , GradientBoostingClassifier(**rs) )
+               , ('Gaussian NB'               , GaussianNB() )
+               , ('Gaussian Process'          , GaussianProcessClassifier(**rs) )
+               , ('K-Nearest Neighbors'       , KNeighborsClassifier() ) 
+               , ('LDA'                       , LinearDiscriminantAnalysis() )
+               , ('Logistic Regression'       , LogisticRegression(**rs) )
+               , ('Logistic RegressionCV'     , LogisticRegressionCV(cv = 3, **rs))
+               , ('MLP'                       , MLPClassifier(max_iter = 500, **rs) ) 
+               , ('Multinomial'               , MultinomialNB() )
+               , ('Naive Bayes'               , BernoulliNB() )
+               , ('Passive Aggresive'         , PassiveAggressiveClassifier(**rs, **njobs) )
+               , ('QDA'                       , QuadraticDiscriminantAnalysis() )
+               , ('Random Forest'             , RandomForestClassifier(**rs, n_estimators = 1000, **njobs ) ) 
+               , ('Random Forest2'            , RandomForestClassifier(min_samples_leaf = 5
+                                                                       , n_estimators     = 1000
+                                                                       , bootstrap        = True
+                                                                       , oob_score        = True
+                                                                       , **njobs
+                                                                       , **rs
+                                                                       , max_features     = 'auto') ) 
+                , ('Ridge Classifier'          , RidgeClassifier(**rs)  )
+                , ('Ridge ClassifierCV'        , RidgeClassifierCV(cv = 3) )          
+                , ('SVC'                       , SVC(**rs) ) 
+                , ('Stochastic GDescent'       , SGDClassifier(**rs, **njobs) )
+                , ('XGBoost'                   , XGBClassifier(**rs, verbosity = 0, use_label_encoder = False, **njobs) )
              ]
                 
     mm_skf_scoresD = {}