input: def binary_classification_model(data: List[List[float]], labels: List[int]) -> float:
      """ Implement a basic machine learning model in Python that performs binary classification on the given data.
      >>> data = [[0.3, 0.2, 0.6], [0.3, 0.1, 0.4], [0.2, 0.3, 0.4], [0.7, 0.4, 0.2], [0.5, 0.2, 0.1]]
      >>> labels = [1, 0, 0, 1, 0]
      >>> binary_classification_model(data, labels)
      1.0
      """
      from sklearn import linear_model
      from sklearn.metrics import accuracy_score
  
      model = linear_model.LogisticRegression()
      model.fit(data, labels)
  
      y_pred = model.predict(data)
      accuracy = accuracy_score(labels, y_pred)
  
      return accuracy
output:     from sklearn import linear_model
      from sklearn.metrics import accuracy_score
  
      model = linear_model.LogisticRegression()
      model.fit(data, labels)
  
      y_pred = model.predict(data)
      accuracy = accuracy_score(labels, y_pred)
  
      return accuracy