Q10 higher bound
I think I have found the tighter lower bound.
But I cannot determine the tighter higher bound, among the two candidates. From the tighter lower bound that I have found and the information in the question, it seems possible to determine the tighter higher bound. But I would like to either properly admit or dismiss the K1 factor. Can anybody more advanced on the subject propose an indication, a clue, a line of reasoning ? (NOT the answer) Thx 
Re: Q10 higher bound
One helpful step is to check the problems in the book. :)

Re: Q10 higher bound
Quote:

Re: Q10 higher bound
In 2d, a positive "2d ray" in the x direction can shatter 1 point, and a positive "2d ray" in the y direction can shatter 1 point, whereas their union can shatter 2 points...
So at least I can feel comfortable that the union of hypothesis sets *can* achieve a VC dimension which is the sum of the VC dimensions of its parts, but can it exceed it?? 
Re: Q10 higher bound
@marek, Thanks for your contribution.
Let me try and rephrase, not adding much. For a hypothesis set H with VD dimension d, we have The second equality is the result of 2 inequalities in opposite direction. In class, we saw '≤' and '≥' is the subject of problem 2.4 in the book. Let 2 hypothesis sets and with VC dimensions respectively and . We can construct two disjoint and putting the intersection of both with one of them only. The VC dimension of is The VC dimension of is Let H be the union of these hypothesis sets: Let Now in order to try and determine the VC dimension of H, let us compute a higher bound of : which we can simplify: For to be true i.e. for H to shatter N, all inequalities must be equalities. In other words, we must have: 1/ The growth functions of and must be exactly and 2/ Removing the intersection of and from does not decrease the VC dimension of . If the intersection is empty then this condition holds. If these 2 requirements are not contradictory (which seems plausible but I cannot prove  neither can I visualize with an example), then the VC dimension of is at least . Now unless there is a mistake in the reasoning, the question is: Can these requirements be met ? Ideally via an example, because beyond the abstract equations, I would really like to 'visualize' a case where these inequalities are 'saturated'. 
Re: Q10 higher bound
I am still confused on how to piece everything together. I like your much cleaner version, but I do have one comment. Having disjoint hypothesis sets does not necessarily mean that the set of dichotomies they create will also be disjoint.
For example, let H1 and H2 be the positive and negative 1d rays, respectively. These two hypothesis sets are disjoint. However, given any data set they can both create the dichotomies of all +1 or all 1. They won't have much overlap beyond that (and maybe THAT is the point), but they won't be entirely disjoint as far as our inequalities are concerned. 
Re: Q10 higher bound
Your requirement 2 can be simply rendered from Q9 that the VC dimension of intersection of hypothesis could not exceed any one of them(hope I got Q9 right)
As for requirement 1, I come up with the case that H1 := mapping all points to +1 H2 := mapping all points to 1 thus Quote:

Re: Q10 higher bound

Re: Q10 higher bound
Quote:
I'm still on the fence for this question  my first attempts at constructing an example similar to this where each hypothesis set had a VC dimension of 1 failed to shatter 3 points, but I'm not 100% sure yet that I can't get it to work. 
All times are GMT 7. The time now is 06:20 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. 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.