input: Write a function to implement a basic machine learning model in Python that performs binary classification on the given data. The function should train a Logistic Regression model using the provided input data and labels, and then print the accuracy of the model on the training data. The function should return nothing.
  
  
  def binary_classification_model(X, y):
      from sklearn import linear_model
      from sklearn.metrics import accuracy_score
  
      model = linear_model.LogisticRegression()
      model.fit(X, y)
  
      y_pred = model.predict(X)
      accuracy = accuracy_score(y, y_pred)
  
      print('Model accuracy:', accuracy)
  
  # Test cases
  X = [[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]]
  y = [1, 0, 0, 1, 0]
  binary_classification_model(X, y)
  
output: def binary_classification_model(X, y):
      from sklearn import linear_model
      from sklearn.metrics import accuracy_score
  
      model = linear_model.LogisticRegression()
      model.fit(X, y)
  
      y_pred = model.predict(X)
      accuracy = accuracy_score(y, y_pred)
  
      print('Model accuracy:', accuracy)