input: 
  from sklearn import linear_model
  from sklearn.metrics import accuracy_score
  
  def binary_classification(X, y):
      """ Implement a basic machine learning model that performs binary classification on the given data.
      >>> binary_classification([[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])
      'Model accuracy: 1.0'
      """
      model = linear_model.LogisticRegression()
      model.fit(X, y)
      y_pred = model.predict(X)
      accuracy = accuracy_score(y, y_pred)
      return f'Model accuracy: {accuracy}'
  
output:     model = linear_model.LogisticRegression()
      model.fit(X, y)
      y_pred = model.predict(X)
      accuracy = accuracy_score(y, y_pred)
      return f'Model accuracy: {accuracy}'