input: 
  def linear_regression_predict(X: List[int], Y: List[int]) -> List[float]:
      """
      Perform linear regression on the given dataset and predict the output for a new input.
      >>> linear_regression_predict([1,2,3,4,5], [3,5,7,9,13])
      [15.0]
      """
      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 a new value of x (e.g., 7)
      return model.predict([[7]])
  
output:     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 a new value of x (e.g., 7)
      return model.predict([[7]])