input: Write a function to perform linear regression for predicting the numbers in a given dataset. The function should take two lists as input, X and Y, and return the predicted value of Y for a new value of X that is predefined.
  
  def linear_regression(X, Y):
      import numpy as np
      from sklearn.linear_model import LinearRegression
      
      X = np.array(X).reshape(-1,1)
      Y = np.array(Y)
      
      model = LinearRegression()
      model.fit(X, Y)
      
      # Predicts the value of y for X = 7
      new_X = [[7]]
      predicted_Y = model.predict(new_X)
      return predicted_Y[0]
  
  assert linear_regression([1, 2, 3, 4, 5], [3, 5, 7, 9, 13]) == 15.0
output: def linear_regression(X, Y):
      import numpy as np
      from sklearn.linear_model import LinearRegression
      
      X = np.array(X).reshape(-1,1)
      Y = np.array(Y)
      
      model = LinearRegression()
      model.fit(X, Y)
      
      new_X = [[7]]
      predicted_Y = model.predict(new_X)
      return predicted_Y[0]