LFD Book Forum  

Go Back   LFD Book Forum > Course Discussions > Online LFD course > Homework 1

Reply
 
Thread Tools Display Modes
  #41  
Old 04-22-2012, 02:40 PM
jmknapp jmknapp is offline
Member
 
Join Date: Apr 2012
Location: Columbus OH USA
Posts: 14
Default Re: Perceptron Learning Algorithm

How is the PLA generalized to handling multi-category classification, e.g., the problem of classifying coins?
Reply With Quote
  #42  
Old 04-22-2012, 08:51 PM
htlin's Avatar
htlin htlin is offline
NTU
 
Join Date: Aug 2009
Location: Taipei, Taiwan
Posts: 601
Default Re: Perceptron Learning Algorithm

Quote:
Originally Posted by jmknapp View Post
How is the PLA generalized to handling multi-category classification, e.g., the problem of classifying coins?
Interesting question. There are general techniques for extending from binary classification to K-category one. For instance, one simple approach (one-versus-all decomposition) is to form the following yes/no questions: "Does an example belong to category k or not?" If the machine learns K hypotheses that answer each of the K questions correctly, you can combine the answers to form a multi-category prediction. Hope this helps.
__________________
When one teaches, two learn.
Reply With Quote
  #43  
Old 04-22-2012, 08:53 PM
htlin's Avatar
htlin htlin is offline
NTU
 
Join Date: Aug 2009
Location: Taipei, Taiwan
Posts: 601
Default Re: Perceptron Learning Algorithm

Quote:
Originally Posted by zsero View Post
There is a point what I think is not clearly explained. It took me a long time to realize that it's not true that exactly one point gets corrected in each step. The true statement is that at most one point gets corrected in each step.
The "at most" part may also be tricky, because you may be using point A for correction but "happens" to correct B and C by moving in a good direction.
__________________
When one teaches, two learn.
Reply With Quote
  #44  
Old 04-22-2012, 09:01 PM
htlin's Avatar
htlin htlin is offline
NTU
 
Join Date: Aug 2009
Location: Taipei, Taiwan
Posts: 601
Default Re: Perceptron Learning Algorithm

Quote:
Originally Posted by shockwavephysics View Post
I have been trying to figure out why updating using w -> w + y_n * x_n works at all. I looked up the relevant section in the text, and there are a series of questions for the student that hint at the answer. I followed that logic to it's conclusion and it does seem to show that updating in that way will always give a w that is better (for the misclassified point) than the previous w. However, I cannot figure out how one comes up with this formulation in the first place. Is there a reference to a derivation I can read?
You can read Problem 1.3 of the recommended textbook, which guides you through a simple proof. Roughly speaking, the proof says the PLA weights get more aligned with the underlying "target weights" after each update.
__________________
When one teaches, two learn.
Reply With Quote
  #45  
Old 04-23-2012, 07:21 PM
jmknapp jmknapp is offline
Member
 
Join Date: Apr 2012
Location: Columbus OH USA
Posts: 14
Default Re: Perceptron Learning Algorithm

Thanks--the textbook should be arriving from Amazon tomorrow.
Reply With Quote
  #46  
Old 10-10-2012, 10:51 PM
ken47 ken47 is offline
Junior Member
 
Join Date: Oct 2012
Posts: 3
Default Re: Perceptron Learning Algorithm

I adapted an implementation of the single-layer perceptron for Octave (open-source Matlab) that I found online. It runs incredibly slow compared to my nodeJS implementation, but one can see the progress graphically which I think is really cool. Gist attached.

http://gist.github.com/3870213.git
Reply With Quote
  #47  
Old 01-12-2013, 03:18 AM
foodcomazzz foodcomazzz is offline
Junior Member
 
Join Date: Jan 2013
Posts: 5
Default Re: Perceptron Learning Algorithm

Thanks so much prof. This thread is very detailed and useful!
Reply With Quote
Reply

Thread Tools
Display Modes

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 Jump


All times are GMT -7. The time now is 01:48 AM.


Powered by vBulletin® Version 3.8.3
Copyright ©2000 - 2019, Jelsoft Enterprises Ltd.
The contents of this forum are to be used ONLY by readers of the Learning From Data book by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, and Hsuan-Tien Lin, and participants in the Learning From Data MOOC by Yaser S. Abu-Mostafa. No part of these contents is to be communicated or made accessible to ANY other person or entity.