Chapter 1  Problem 1.3
I am a bit stuck on part b. I am not sure how to start. Could anyone give a nudge in the right direction?

Re: Chapter 1  Problem 1.3
Quote:

Re: Chapter 1  Problem 1.3
Can you please do the proof for this problem, I can answer the question conceptually but mathematically I'm having a little trouble starting my argument for both part a and part b please :bow:

Re: Chapter 1  Problem 1.3
Quote:
http://www.csie.ntu.edu.tw/~htlin/co...02_handout.pdf 
Re: Chapter 1  Problem 1.3
Hi I can solve the problem but I cannot understand how does this show that the perceptron algorithm will converge. Can somone explains to me what does the proof shows? I mean what does each step of the problems mean? Thanks

Re: Chapter 1  Problem 1.3
Despite the slides I still have difficulty reading the equations.
In my PLA program weights are updated by "the difference between the 'target function line' and x2" for a misclassified example from a 2dimensional space. Example target function line: 2 + 3x. If x1 = 3 en x2 = 9, y = 9 (2+3*3) = 2 If misclassified the weights would be updated like: wt+1 = wt + x1 * 2 The method above maybe omits advantages of vector computation(?) as seen in the slides, but I was happy the simulation worked at all:) The theoretic approach of this course seems more useful in the long term than 'simply learning to type methods', but for me is new and challenging. So my questions are:  is p a random symbol? I can't find it in the overview.  does min1 < n < N stand for the sum of function (x) in range N?  is yn the positive or negative difference between the target line and coordinate x2 (staying with the 2dimensional graphical model)?  I understand a little simple linear algebra for linear regression. Are vector computations making the understanding of this PLA equation easier? Thanks in advance! 
Re: Chapter 1  Problem 1.3
3 Attachment(s)
Hi, I am stuck at the part (e). I have two questions:
1  Is R' a typo? If R' is R then: 2  Refer to (b), I observe that: http://book.caltech.edu/bookforum/at...1&d=1458721054 Refer to (c), I observe that: http://book.caltech.edu/bookforum/at...1&d=1458720991 But I think that http://book.caltech.edu/bookforum/at...1&d=1458721179 happens only when t <= 1? Am I mistaken somewhere? 
Re: Chapter 1  Problem 1.3
Quote:
2. (c) works well for t>=0. Do not refer from (b) to (c). Try to refer to the previously proven inequality (so, from (c) to (b)). 
Re: Chapter 1  Problem 1.3
Quote:

All times are GMT 7. The time now is 08:31 PM. 
Powered by vBulletin® Version 3.8.3
Copyright ©2000  2021, Jelsoft Enterprises Ltd.
The contents of this forum are to be used ONLY by readers of the Learning From Data book by Yaser S. AbuMostafa, Malik MagdonIsmail, and HsuanTien Lin, and participants in the Learning From Data MOOC by Yaser S. AbuMostafa. No part of these contents is to be communicated or made accessible to ANY other person or entity.