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 logistic regression from the sklearn library and print the model 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])==0.8
output: def binary_classification_model(X, y):
      from sklearn.linear_model import LogisticRegression
      from sklearn.metrics import accuracy_score
  
      model = LogisticRegression()
      model.fit(X, y)
      y_pred = model.predict(X)
      accuracy = accuracy_score(y, y_pred)
      print(accuracy)
      return accuracy