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gibson:teaching:fall-2014:math445:lab5 [2014/11/13 06:43]
gibson
gibson:teaching:fall-2014:math445:lab5 [2015/03/09 13:39]
gibson
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 </​code>​ </​code>​
  
-or equivalently 
- 
-<​code>​ 
-N=100; 
-p=(G^N)*p; 
-</​code>​ 
  
 After that is complete the elements of ''​p''​ give the probabilities that a random web surfer will end up at the web pages listed in ''​U'',​ and you can rank the pages in ''​U''​ according to their probabilities in ''​p''​. Look up the ''​sort''​ command in the Help menu and find a way to print the list of websites in order of their rank. Turn in the list of the top 10, the fraction of the time a random web surfer would spend in each one of those 10, and your code to complete the Lab.  After that is complete the elements of ''​p''​ give the probabilities that a random web surfer will end up at the web pages listed in ''​U'',​ and you can rank the pages in ''​U''​ according to their probabilities in ''​p''​. Look up the ''​sort''​ command in the Help menu and find a way to print the list of websites in order of their rank. Turn in the list of the top 10, the fraction of the time a random web surfer would spend in each one of those 10, and your code to complete the Lab. 
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-Now write a script that tests and times these algorithms on link matrices L of sizes M = 32, 64, 128, 256, 512and 1024. It's smart to develop and test your code on a smaller set of M, perhaps just M = 32, 64, 128, and 256. As a starting point, here's the code we developed in class to measure execution time of full versus sparse matrices.+Now write a script that tests and times these algorithms on link matrices L of sizes M = 32, 64, 128, 256, ....up to whatever power of two your computer can handle. It's smart to develop and test your code on a smaller set of M, perhaps just M = 32, 64, 128. As a starting point, here's the code we developed in class to measure execution time of full versus sparse matrices.
  
 <code matlab> <code matlab>
gibson/teaching/fall-2014/math445/lab5.txt ยท Last modified: 2015/03/09 13:39 by gibson