input: from typing import List, Tuple
  from sklearn.svm import SVC
  from sklearn.metrics import accuracy_score
  
  def evaluate_model_accuracy(clf: SVC, X_train: List[List[float]], y_train: List[float], X_test: List[List[float]], y_test: List[float]) -> float:
      """Evaluate the accuracy of a machine-learning model using the given parameters.
      >>> X_train = [[0, 0], [1, 1]]
      >>> y_train = [0, 1]
      >>> X_test = [[2, 2]]
      >>> y_test = [1]
      >>> clf = SVC(kernel='poly', degree=2, gamma=0.05)
      >>> evaluate_model_accuracy(clf, X_train, y_train, X_test, y_test)
      1.0
      """
      clf.fit(X_train, y_train)
      y_pred = clf.predict(X_test)
      accuracy = accuracy_score(y_test, y_pred)
      return accuracy
output:     clf.fit(X_train, y_train)
      y_pred = clf.predict(X_test)
      accuracy = accuracy_score(y_test, y_pred)
      return accuracy