LFD Book Forum  

Go Back   LFD Book Forum > Book Feedback - Learning From Data > Chapter 3 - The Linear Model

 
 
Thread Tools Display Modes
Prev Previous Post   Next Post Next
  #1  
Old 10-13-2014, 09:14 AM
mddsangster mddsangster is offline
Junior Member
 
Join Date: Oct 2014
Posts: 4
Default Pocket Algorithm

I'm working on coding the pocket algorithm, however I feel I have hit an impasse. I'm not sure if it is a bug in my code or a flaw in the inherent structure of the pocket algorithm, but when testing the code on a known linearly separable data set, the algorithm often 'settles' on a non-optimal weight vector (i.e. one where Ein != 0). I believe this is due to the fact that the algorithm does not allow for weights producing higher values of Ein even if those values may later lead to an even lower Ein.

So, what I'm asking is, should the pocket algorithm always be able to find a linear classifier that separates separable data?
Reply With Quote
 

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 03:47 PM.


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.