input: Write a function to develop a machine learning algorithm in Python that identifies apples from bananas. The function should load the provided data, initialize a classifier, fit the data, and test the classifier's predictions on new data. The output should be the predicted labels for the test data.
  assert identify_fruit(__import__('io').StringIO('import numpy as np\nfrom sklearn.svm import SVC\n\n# Load data\nX = np.array([[1,2,3], [-1,2,5], [-1,2,7], [5,5,5], [3,3,3], [5,5,7]])\ny = np.array([0, 0, 0, 1, 0, 1])\n\n# Initialize classifier\nclf = SVC(kernel=\'linear\')\n\n# Fit data\nclf.fit(X, y)\n\n# Test classifier\nx_test = np.array([[2,2,2], [4,4,4]])\n\nprediction = clf.predict(x_test)\nprint(prediction)'))==[0, 1]
output: def identify_fruit(data):
      exec(data.read())
      return prediction