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 Logistic Regression model from sklearn and print the model's accuracy.
  
  
  def binary_classification(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(X, y)
  
output: def binary_classification(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)