input: from typing import List
  
  def predict_fruit(X: List[List[int]], y: List[int], x_test: List[List[int]]) -> List[int]:
      """ A machine learning algorithm to identify apples (class 0) and bananas (class 1).
      The function uses a Support Vector Classifier (SVC) with a linear kernel.
      
      >>> X = [[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]]
      >>> y = [0, 0, 0, 1, 0, 1]
      >>> x_test = [[2,2,2], [4,4,4]]
      >>> predict_fruit(X, y, x_test)
      [0, 1]
      """
      import numpy as np
      from sklearn.svm import SVC
  
      clf = SVC(kernel='linear')
      clf.fit(X, y)
      prediction = clf.predict(x_test)
      return prediction
output:     import numpy as np
      from sklearn.svm import SVC
  
      clf = SVC(kernel='linear')
      clf.fit(X, y)
      prediction = clf.predict(x_test)
      return prediction