input: def binary_classification_model(X: List[List[float]], y: List[int]) -> linear_model.LogisticRegression:
      """ Implements a basic machine learning model that performs binary classification
      on the given data using logistic regression. Returns the trained model.
      
      >>> 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]
      >>> model = binary_classification_model(X, y)
      >>> y_pred = model.predict(X)
      >>> accuracy = accuracy_score(y, y_pred)
      >>> print('Model accuracy:', accuracy)
      Model accuracy: 1.0
      """
      model = linear_model.LogisticRegression()
      model.fit(X, y)
      return model
output:     from sklearn import linear_model
      from sklearn.metrics import accuracy_score