diff --git a/compare_models_10k.py b/compare_models_10k.py
index 7916541..1f28b02 100644
--- a/compare_models_10k.py
+++ b/compare_models_10k.py
@@ -29,7 +29,7 @@ from sklearn.neural_network import MLPClassifier
 
 set_config(transform_output="pandas") # dataframe supremacy
 
-jobs = 12
+jobs = 4
 max_iter = 3000
 min_entries = 5
 
@@ -121,14 +121,14 @@ datasets = [
 estimators = {
     #"RidgeClassifier": RidgeClassifier(random_state=0, max_iter=max_iter),
     #"PassiveAggressiveClassifier": PassiveAggressiveClassifier(random_state=0, max_iter=max_iter),
-    "Perceptron": Perceptron(random_state=0, max_iter=max_iter),
-    "SGDClassifier": SGDClassifier(random_state=0, max_iter=max_iter),
-    "NearestCentroid": NearestCentroid(),
-    "LinearSVC": LinearSVC(random_state=0, max_iter=max_iter),
-    "GradientBoostingClassifier": GradientBoostingClassifier(random_state=0),
+    #"Perceptron": Perceptron(random_state=0, max_iter=max_iter),
+    #"SGDClassifier": SGDClassifier(random_state=0, max_iter=max_iter),
+    #"NearestCentroid": NearestCentroid(),
+    #"LinearSVC": LinearSVC(random_state=0, max_iter=max_iter),
+    #"GradientBoostingClassifier": GradientBoostingClassifier(random_state=0),
     "HistGradientBoostingClassifier": HistGradientBoostingClassifier(random_state=0, max_iter=max_iter),
-    "LinearDiscriminantAnalysis": LinearDiscriminantAnalysis(),
-    "MLPClassifier": MLPClassifier(random_state=0, max_iter=int(max_iter/20), early_stopping=True),
+    #"LinearDiscriminantAnalysis": LinearDiscriminantAnalysis(),
+    #"MLPClassifier": MLPClassifier(random_state=0, max_iter=int(max_iter/20), early_stopping=True),
 }
 
 #"VotingClassifier": VotingClassifier(estimators=[('lr', LogisticRegression()), ('rf', RandomForestClassifier())]),