input: def train_binary_classification_model(data: List[List[float]]) -> None:
      """ Implement a basic machine learning model in Python that performs binary classification on the given data.
      >>> train_binary_classification_model([
      ... [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]
      ... ])
      Model accuracy: 0.8
      """
output:     from sklearn.model_selection import train_test_split
      from sklearn.linear_model import LogisticRegression
      from sklearn.metrics import accuracy_score
  
      X = [row[:-1] for row in data]
      y = [row[-1] for row in data]
  
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
  
      model = LogisticRegression()
      model.fit(X_train, y_train)
  
      y_pred = model.predict(X_test)
      accuracy = accuracy_score(y_test, y_pred)
  
      print(f"Model accuracy: {accuracy:.1f}")