input: from typing import Tuple
  
  def evaluate_accuracy(X_train, y_train, X_test, y_test) -> float:
      """ Evaluate the accuracy of a machine-learning model using Support Vector Classifier (SVC).
      The model is trained with polynomial kernel of degree 2 and gamma set to 0.05.
      >>> from sklearn.svm import SVC
      >>> clf = SVC(kernel='poly', degree=2, gamma=0.05)
      >>> X_train, y_train, X_test, y_test = load_data() # Assume load_data loads appropriate data for training and testing
      >>> evaluate_accuracy(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:     from sklearn.svm import SVC
      from sklearn.metrics import accuracy_score
      
      clf = SVC(kernel='poly', degree=2, gamma=0.05)