from sklearn.datasets import load_iris
from sklearn.tree import DecisionTreeClassifier

# Load the iris dataset
iris = load_iris()

# Train the decision tree classifier
clf = DecisionTreeClassifier()
clf.fit(iris.data, iris.target)

# Predict the target values of new data
new_data = [[5.0, 3.6, 1.4, 0.2], [6.0, 2.2, 4.0, 1.0], [7.2, 3.2, 6.0, 1.8]]
predicted = clf.predict(new_data)

print(predicted)