input: 
  def binary_classification_model(X: List[List[float]], y: List[int]) -> float:
      """Implement a basic machine learning model that performs binary classification on the given data.
      The function uses a Logistic Regression model from the sklearn library and returns the model's accuracy.
      >>> 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])
      1.0
      """
      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)
      
      return accuracy
  
output:     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)
      
      return accuracy