input: 
  from sklearn.svm import SVC
  from sklearn.metrics import accuracy_score
  
  def evaluate_model_accuracy(clf: SVC, X_train, y_train, X_test, y_test) -> float:
      """
      Evaluate the accuracy of a given machine-learning model.
      
      >>> clf = SVC(kernel='poly', degree=2, gamma=0.05)
      >>> evaluate_model_accuracy(clf, X_train, y_train, X_test, y_test)
      0.95
      """
      clf.fit(X_train, y_train)
      y_pred = clf.predict(X_test)
      return accuracy_score(y_test, y_pred)
  
output:     clf.fit(X_train, y_train)
      y_pred = clf.predict(X_test)
      return accuracy_score(y_test, y_pred)