Re: on the right track?
Quote:
Quote:

Re: on the right track?
@Sendai
What values for Ein do you get when running your algorithm with Lloyds centers? I think I am still somewhere off the track :( 
Re: on the right track?
centres = [[ 0., 0.], [ 0.66666667, 0.66666667]]
Ein = 0 centres = [[ 0.66666667, 0.33333333], [ 0., 1.]] Ein = 0 centres = [[ 1. , 0.5], [ 0. , 0.5]] Ein = 0.5 (The weight are all zeros  RBF can't break the symmetry and fails.) 
Re: on the right track?
I had a difficult bug to find here, in R. Beware, other R users. I ran the first example, and it was just fine. I ran the second example, and got nothing like the right answer. What? said me.
I had been using my own linear regression program, since it was conveniently to hand. But I knew it worked. So I tried the builtin R linear regression, which gave the correct answer. I noticed that in my own linear regression, I was calling ginv, the pseudoinverse function. I called solve, the actual inverse function (why you get the inverse of a square matrix by calling "solve" is beyond me, but I digress). That worked. Finally I realized that our little example is quite a nasty matrix. The tolerance for ginv was something like 1E8. Not small enough! Once I lowered the tolerance, everything was dandy. 
Re: on the right track?
Thanks heer2351 and Sendai. Indeed there are 6 different centreconfigurations, the ones you gave complete the picture. You can also see this with paper&pencil.
Quote:
Anything else you get, you know your code has a bug. I have not tried it with my code, but Sendai's results seem correct. So you should get Ein =0 for the centres that have 1/3 or 2/3 in them (when the clusters are 31 points) and Ein = 0.5 when the centres have 1/2 in them (the case were the clusters are 22points) I also think that it might be impossible to get Ein= 0.25 for any centre configuration, providing that the weights are chosen optimally (i.e., using the pseudo inverse method). So you either make no mistakes, or 2 points are misclassified. 
Re: on the right track?
Quote:
Code:
[[ 1. 0.96078944 0.22537266] 
Re: on the right track?
Sendai thanks for starting this thread, it enabled me to find a flaw in my code and even better fix it :)
All answers I found with my fixed code were correct. Special thanks to boulis for his first response, I was overthinking the problem. 
Re: on the right track?
Ah ha, I see how you got that but I think that you need to take the square root after you add up the distance of each data point to the cluster centers. You did not take the square root. I think you have to IMHO.
Quote:

Re: on the right track?
Quote:

All times are GMT 7. The time now is 09:59 AM. 
Powered by vBulletin® Version 3.8.3
Copyright ©2000  2020, 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.