input: Write a function to classify a dataset using SVM with a linear kernel and C=0.1.
  assert classify_dataset([[1, 2], [2, 3], [3, 4], [4, 5]], [0, 1, 0, 1]).tolist() == [0, 1]
  assert classify_dataset([[5, 6], [6, 7], [7, 8], [8, 9]], [1, 0, 1, 0]).tolist() == [1, 0]
  assert classify_dataset([[1, 1], [2, 2], [3, 3], [4, 4]], [0, 0, 1, 1]).tolist() == [0, 1]
output: def classify_dataset(X, y):
      from sklearn.svm import SVC
      model = SVC(kernel='linear', C=0.1)
      model.fit(X, y)
      return model.predict(X)