input: Write a function to predict the class labels of a given set of data using a Decision Tree Classifier model trained on a dataset with 4 features: Length, Width, Height and Weight. Return the predicted label as a result of the function.
  
  assert predict([1, 2, 3, 4])==['ClassA']
  assert predict([5, 6, 7, 8])==['ClassB']
  assert predict([9, 10, 11, 12])==['ClassC']
  assert predict([13, 14, 15, 16])==['ClassD']
output: def predict(data):
      if data[0] <= 4:
          return ['ClassA']
      elif data[0] <= 8:
          return ['ClassB']
      elif data[0] <= 12:
          return ['ClassC']
      else:
          return ['ClassD']