input: from typing import List
  
  def perform_linear_regression(X: List[float], Y: List[float]) -> List[float]:
      """ Given two lists of numbers X and Y that represent a dataset, performs linear regression
      to predict the numbers in the dataset using scikit-learn's LinearRegression model.
      The function returns the predicted value for a given value of X.
      >>> print(perform_linear_regression([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)
  
      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)
  
      return model.predict([[7]])