Naive recursive solution Implement the naive cut rod algorithm using pure recursive strategy. Note that the price for length i is stored as the list element prices[i-1] . In [ ]: def naive_rod_cutting(prices, n): if n == 0: return e 9 = float("-inf") ### START YOUR CODE ### for i in None: # Specify the range 9 - None ### END YOUR CODE ### return a In [ ]: # DO not change the test code here prices = [1, 5, 8, 9, 10, 17, 17, 20, 24, 30] print('max revenue:', naive_rod_cutting(prices, 9)) Expected output: max revenue: 25

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
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Naive recursive solution
Implement the naive cut rod algorithm using pure recursive strategy. Note that the price for length i is stored as the list element prices[i-1] .
In [ ]: def naive_rod_cutting(prices, n):
if n == 0:
return e
q = float("-inf")
### START YOUR CODE ###
for i in None: # Specify the range
9 = None
### END YOUR CODE ###
return a
In [ ]: # Do not change the test code here
prices = [1, 5, 8, 9, 10, 17, 17, 20, 24, 30]
print('max revenue:', naive_rod_cutting(prices, 9))
Expected output:
max revenue: 25
Transcribed Image Text:Naive recursive solution Implement the naive cut rod algorithm using pure recursive strategy. Note that the price for length i is stored as the list element prices[i-1] . In [ ]: def naive_rod_cutting(prices, n): if n == 0: return e q = float("-inf") ### START YOUR CODE ### for i in None: # Specify the range 9 = None ### END YOUR CODE ### return a In [ ]: # Do not change the test code here prices = [1, 5, 8, 9, 10, 17, 17, 20, 24, 30] print('max revenue:', naive_rod_cutting(prices, 9)) Expected output: max revenue: 25
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