input: 
  def linear_regression_predict(X, Y):
      """Perform linear regression for predicting the values in the given dataset.
      The function uses sklearn's LinearRegression model to fit the data and 
      predict the target values.
      
      Example:
      >>> linear_regression_predict([1,2,3,4,5], [3,5,7,9,13])
      [17.]
      """
      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
      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
      return model.predict([[7]])