input: from typing import List, Union
  
  def predict_class_labels(data: List[Union[int, float]]) -> int:
      """ Predict the class labels of a given set of data.
      The dataset contains 4 features: Length, Width, Height, and Weight.
      >>> predict_class_labels([12, 8, 6, 200])
      1
      >>> predict_class_labels([15, 10, 8, 250])
      0
      """
      # Load the dataset
      import pandas as pd
      csv_url = 'http://test.test/test.csv'
      df = pd.read_csv(csv_url)
  
      # Split the dataset into features and label
      X = df.iloc[:, 0:4].values
      y = df.iloc[:, 4].values
  
      # Import the ML model
      from sklearn.tree import DecisionTreeClassifier
  
      # Create and fit the model
      model = DecisionTreeClassifier()
      model.fit(X, y)
  
      # Predict the label
      predicted_label = model.predict([data])
      return predicted_label[0]
output:     # Load the dataset
      import pandas as pd
      csv_url = 'http://test.test/test.csv'
      df = pd.read_csv(csv_url)
  
      # Split the dataset into features and label
      X = df.iloc[:, 0:4].values
      y = df.iloc[:, 4].values
  
      # Import the ML model
      from sklearn.tree import DecisionTreeClassifier
  
      # Create and fit the model
      model = DecisionTreeClassifier()
      model.fit(X, y)
  
      # Predict the label
      predicted_label = model.predict([data])
      return predicted_label[0]