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)
