input: from typing import List
  
  def linear_regression(X: List[int], Y: List[int]) -> float:
      """
      Perform linear regression for predicting the numbers in a given dataset using scikit-learn.
      X is the list of independent variable values and Y is the list of corresponding dependent variable values.
      The function fits a linear model using the given data and predicts the value of Y for a new X value.
      
      >>> linear_regression([1, 2, 3, 4, 5], [3, 5, 7, 9, 13])
      [14.9]
      """
      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
      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 X = 7
      return model.predict([[7]])