input: 
  def predict(data):
      """
      Predicts the class label of a given set of data containing 4 features: Length, Width, Height, and Weight.
  
      >>> from io import StringIO
      >>> import pandas as pd
      >>> csv_data = 'Length,Width,Height,Weight,Label\\n5,3,8,2,1\\n10,6,14,5,2'
      >>> df = pd.read_csv(StringIO(csv_data))
      >>> X = df.iloc[:, 0:4].values
      >>> y = df.iloc[:, 4].values
      >>> model = DecisionTreeClassifier()
      >>> model.fit(X, y)
      >>> predict([5, 3, 8, 2])
      [1]
      >>> predict([10, 6, 14, 5])
      [2]
      """
      global model  # Ensure we use the same model as in the initial setup
      predicted_label = model.predict([data])
      return predicted_label
  
output:     global model  # Ensure we use the same model as in the initial setup
      predicted_label = model.predict([data])
      return predicted_label