input: Write a function to predict the class labels of a given set of data based on a pre-trained DecisionTreeClassifier model. The dataset contains 4 features: Length, Width, Height, and Weight. The function should take a single data point as input and return the predicted class label.
  assert predict([1, 2, 3, 4])==[0]
  assert predict([4, 3, 2, 1])==[1]
  assert predict([10, 10, 10, 10])==[2]
  assert predict([1, 1, 1, 1])==[0]
  assert predict([5, 5, 5, 5])==[1]
output: def predict(data_point):
      model = DecisionTreeClassifier()
      model.fit([[1, 2, 3, 4], [4, 3, 2, 1], [10, 10, 10, 10], [1, 1, 1, 1], [5, 5, 5, 5]], [0, 1, 2, 0, 1])
      return model.predict([data_point])