input: from typing import Tuple
  
  def evaluate_model_accuracy(model, X_train: np.ndarray, y_train: np.ndarray, X_test: np.ndarray, y_test: np.ndarray) -> Tuple[float, float]:
      """ Evaluate the accuracy of a given machine-learning model. Fits the model on training data and
      calculates the accuracy on the test data.
      >>> clf = SVC(kernel='poly', degree=2, gamma=0.05)
      >>> X_train, y_train, X_test, y_test = np.array([...]), np.array([...]), np.array([...]), np.array([...])
      >>> accuracy = evaluate_model_accuracy(clf, X_train, y_train, X_test, y_test)
      >>> print(accuracy)
      (Accuracy, Accuracy_Score)
      """
      model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      return accuracy_score(y_test, y_pred)
output:     model.fit(X_train, y_train)
      y_pred = model.predict(X_test)
      accuracy = accuracy_score(y_test, y_pred)
      return accuracy, accuracy