input: Write a function to develop a machine learning algorithm in Python to identify apples from bananas. The function should initialize a classifier, fit it to the given data, and return the predictions for new data.
  assert identify_fruits(np.array([[2,2,2], [4,4,4]])) == [0, 1]
output: def identify_fruits(new_data):
      import numpy as np
      from sklearn.neighbors import KNeighborsClassifier
      
      # Sample training data
      X_train = np.array([[1, 1, 1], [3, 3, 3]])
      y_train = np.array([0, 1])  # 0 for apple, 1 for banana
      
      # Initialize the classifier
      classifier = KNeighborsClassifier(n_neighbors=1)
      
      # Fit the classifier to the training data
      classifier.fit(X_train, y_train)
      
      # Return predictions for new data
      return classifier.predict(new_data).tolist()