@@ -0,0 +1,355 @@
+import milk.supervised.tree%0Aimport numpy as np%0Aimport tests.data.german.german%0A%0Adef test_tree():%0A    data = tests.data.german.german.load()%0A    features = data%5B'data'%5D%0A    labels = data%5B'label'%5D%0A    C = milk.supervised.tree.tree_classifier()%0A    C.train(features,labels)%0A    assert ((np.array(%5BC.apply(f) for f in features%5D) %3E .5) == labels).mean() %3E .5%0A%0A

Test tree for >50% accuracy