LFD Book Forum Hw5 q8 data permutation
 User Name Remember Me? Password
 Register FAQ Calendar Mark Forums Read

 Thread Tools Display Modes
#1
05-04-2013, 06:03 PM
 marek Member Join Date: Apr 2013 Posts: 31
Hw5 q8 data permutation

I must be missed something, but I do not understand why we permute the data.

treats each data point separately, but then sums them all up. Thus, even if we do permute the data points, in the end it all gets combined together in this sum. What am I overlooking?
#2
05-04-2013, 07:21 PM
 yaser Caltech Join Date: Aug 2009 Location: Pasadena, California, USA Posts: 1,478
Re: Hw5 q8 data permutation

Quote:
 Originally Posted by marek I must be missed something, but I do not understand why we permute the data. treats each data point separately, but then sums them all up. Thus, even if we do permute the data points, in the end it all gets combined together in this sum. What am I overlooking?
Ture. If we were applying batch mode, permutation would not change anything since the weight update is done at the end of the epoch and takes all the examples into consideration regardless of the order they were presented. In Stochastic gradient descent, however, the update is done after each example, so the order changes the outcome. These permutations ensure that the order is randomized so we get the benefits of randomness that were mentioned briefly in Lecture 9.
__________________
Where everyone thinks alike, no one thinks very much
#3
05-04-2013, 08:03 PM
 marek Member Join Date: Apr 2013 Posts: 31
Re: Hw5 q8 data permutation

Quote:
 Originally Posted by yaser Ture. If we were applying batch mode, permutation would not change anything since the weight update is done at the end of the epoch and takes all the examples into consideration regardless of the order they were presented. In Stochastic gradient descent, however, the update is done after each example, so the order changes the outcome. These permutations ensure that the order is randomized so we get the benefits of randomness that were mentioned briefly in Lecture 9.
I was just about to delete my post as I figured out my error. I missed the "stochastic" part and had not yet watched lecture 10. That's what I get for trying to solve the homework before learning all the material =) Thanks so much for your quick reply

 Thread Tools Display Modes Linear Mode

 Posting Rules You may not post new threads You may not post replies You may not post attachments You may not edit your posts BB code is On Smilies are On [IMG] code is On HTML code is Off Forum Rules
 Forum Jump User Control Panel Private Messages Subscriptions Who's Online Search Forums Forums Home General     General Discussion of Machine Learning     Free Additional Material         Dynamic e-Chapters         Dynamic e-Appendices Course Discussions     Online LFD course         General comments on the course         Homework 1         Homework 2         Homework 3         Homework 4         Homework 5         Homework 6         Homework 7         Homework 8         The Final         Create New Homework Problems Book Feedback - Learning From Data     General comments on the book     Chapter 1 - The Learning Problem     Chapter 2 - Training versus Testing     Chapter 3 - The Linear Model     Chapter 4 - Overfitting     Chapter 5 - Three Learning Principles     e-Chapter 6 - Similarity Based Methods     e-Chapter 7 - Neural Networks     e-Chapter 8 - Support Vector Machines     e-Chapter 9 - Learning Aides     Appendix and Notation     e-Appendices

All times are GMT -7. The time now is 03:03 AM.

 Contact Us - LFD Book - Top