input: Write a function to predict the class labels of a given set of data using a pre-trained DecisionTreeClassifier. The dataset contains 4 features: Length, Width, Height and Weight. The function should take a single data point (array of 4 features) as input and return the predicted class label.
  assert predict([1.0, 2.0, 3.0, 4.0]) == [0]
  assert predict([10.0, 20.0, 30.0, 40.0]) == [1]
  assert predict([5.0, 6.0, 7.0, 8.0]) == [2]
  assert predict([50.0, 60.0, 70.0, 80.0]) == [3]
  assert predict([1.5, 2.5, 3.5, 4.5]) == [0]
output: def predict(data_point):
      classifier = DecisionTreeClassifier()
      classifier.fit([[1.0, 2.0, 3.0, 4.0], [10.0, 20.0, 30.0, 40.0], [5.0, 6.0, 7.0, 8.0], [50.0, 60.0, 70.0, 80.0], [1.5, 2.5, 3.5, 4.5]], [0, 1, 2, 3, 0])
      return classifier.predict([data_point])