diff --git a/data analysis/analysis/analysis.py b/data analysis/analysis/analysis.py
index dbe35ec6..5d58ee3d 100644
--- a/data analysis/analysis/analysis.py	
+++ b/data analysis/analysis/analysis.py	
@@ -7,10 +7,12 @@
 #    current benchmark of optimization: 1.33 times faster
 # setup:
 
-__version__ = "1.1.6.000"
+__version__ = "1.1.6.001"
 
 # changelog should be viewed using print(analysis.__changelog__)
 __changelog__ = """changelog:
+1.1.6.001:
+    - added additional hyperparameters to decisiontree()
 1.1.6.000:
     - fixed __version__
     - fixed __all__ order
@@ -391,10 +393,10 @@ def pca(data, kernel = sklearn.decomposition.PCA(n_components=2)):
 
     return kernel.fit_transform(data)
 
-def decisiontree(data, labels, test_size = 0.3): #expects 2d data and 1d labels
+def decisiontree(data, labels, test_size = 0.3, criterion = "gini", splitter = "default", max_depth = None): #expects 2d data and 1d labels
 
     data_train, data_test, labels_train, labels_test = sklearn.model_selection.train_test_split(data, labels, test_size=test_size, random_state=1)
-    model = sklearn.tree.DecisionTreeClassifier()
+    model = sklearn.tree.DecisionTreeClassifier(criterion = criterion, splitter = splitter, max_depth = max_depth)
     model = model.fit(data_train,labels_train)
     predictions = model.predict(data_test)
     accuracy = sklearn.metrics.accuracy_score(labels_test, predictions)