input: Write a function to develop a machine learning algorithm in Python to identify apples from bananas using a Support Vector Machine with a linear kernel. The function should define the data, initialize and train the classifier, and then test it with sample data.
  assert identify_fruits([[2,2,2], [4,4,4]])==[0, 1]
  assert identify_fruits([])==[]
  assert identify_fruits([[1,2,3]])==[0]
  assert identify_fruits([[-1,2,5]])==[0]
  assert identify_fruits([[5,5,5]])==[1]
output: def identify_fruits(data):
      if not data:
          return []
      X = [[2, 2, 2], [4, 4, 4]]
      y = [0, 1]
      clf = SVC(kernel='linear')
      clf.fit(X, y)
      predictions = clf.predict(data)
      return predictions.tolist()