input: Write a python function to predict the value for Day11 given the values of Day1 through Day10 using linear regression.
  assert predict_day11([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) == 11.0  # Example assertion, replace with actual expected value
  assert predict_day11([10, 9, 8, 7, 6, 5, 4, 3, 2, 1]) == 2.0   # Example assertion, replace with actual expected value
  assert predict_day11([5, 5, 5, 5, 5, 5, 5, 5, 5, 5]) == 5.0    # Example assertion, replace with actual expected value
output: def predict_day11(values):
      from sklearn.linear_model import LinearRegression
      import numpy as np
  
      X = np.arange(1, 11).reshape(-1, 1)  # Days 1 to 10 as features
      y = np.array(values)  # Corresponding values
  
      model = LinearRegression()
      model.fit(X, y)
  
      day11 = np.array([[11]])
      prediction = model.predict(day11)
  
      return prediction[0]