input: Write a python function to train a DecisionTreeClassifier using given features and target data.
  assert isinstance(train_decision_tree(pd.DataFrame({'feature1': [1], 'feature2': [2], 'feature3': [3]}), pd.DataFrame({'target': [0]})), DecisionTreeClassifier)
  assert isinstance(train_decision_tree(pd.DataFrame({'feature1': [4, 5], 'feature2': [6, 7], 'feature3': [8, 9]}), pd.DataFrame({'target': [1, 0]})), DecisionTreeClassifier)
output: def train_decision_tree(features, target):
      from sklearn.tree import DecisionTreeClassifier
      model = DecisionTreeClassifier()
      model.fit(features, target)
      return model