input: Write a function to implement a basic machine learning model in Python that performs binary classification on the given data. The function should use the LogisticRegression model from sklearn and print the accuracy of the model on the training data.
  
  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)
  
  assert 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]], [1, 0, 0, 1, 0])==None
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)