train_data = np.delete(iris.data, test_idx, axis=0) #testing data test_target = iris.target[test_idx] test_data = iris.data[test_idx] #train a classifier clf = tree.DecisionTreeClassifier() clf.fit(train_data, train_target) #these should match print("these should match") print(test_target) print(clf.predict(test_data)) # viz code dot_data = StringIO() tree.export_graphviz(clf, out_file = dot_data, feature_names =iris.feature_names, class_names=iris.target_names, filled=True, rounded=True, impurity=False) graph = pydot.graph_from_dot_data(dot_data.get_value()) graph.write_pdf("iris.pdf") print(test_data[0], test_target[0]) print(iris.feature_names, iris.target_names)