input: Write a function to analyze a dataset of customers and create a classification model in scikit-learn to determine customer churn.
  
  assert churn_classification([3, 4, 5, 1, 2])==True
  assert churn_classification([3, 5, 10, 1, 2])==True
  assert churn_classification([4, 3, 1, 2])==False
  assert churn_classification([3, 5, 4, 1, 2])==False
  assert churn_classification([])==True
output: def churn_classification(data):
      if not data:
          return True
      churn_threshold = 3
      churn_count = sum(1 for x in data if x > churn_threshold)
      return churn_count > len(data) / 2