#21




Re: on the right track?
Quote:
As I try to figure out what's going wrong, I guess I have one initial question. What are we supposed to do with h, should we leave it at 1 as by default? h 0 has no impact on the earlier questions but dramatically changes my answers for Q5 and Q6... and also takes incredibly long to compute. Also regardless of which setting I choose, I always get the warning for hitting the max number of iterations... Any clues as to why that is or how I can prevent that? Edit: Nevermind, after hours of trying to figure it out, minutes after I make a post I discover I had fat fingered d 22 instead of d 2. However, I am still curious as to what the effect of h is if anyone knows. 
#22




Re: on the right track?
Quote:
SVM model for 0vs7 classification with C = 0.01 and Q = 2: SVs = 861 Ein = 0.07177814 Eout = 0.06324111 SVM model for 2vs8 classification with C = 0.1 and Q = 3: SVs = 722 Ein = 0.2348782 Eout = 0.2912088 
#23




Re: on the right track?
I'm stuck halfway in this problem. I'm trying to use the C# version of libsvm and, I think it's working, but I can't corroborate the numbers I'm seeing here. Actually, I match on the # of support vectors, but my Ein and Eout numbers are significantly different.
For 0 vs. 7 with Q=2 and C=.01 I get 861 SVs but using Sign(svm_predict) and counting sign mismatches I get: Ein=.060 and Eout=.057 Looking at 2 vs 8 with C=.1 and Q=3, I get 721 SVs but errors are much worse: Ein=.67 Eout=.63 Since I'm getting the right number of support vectors, I think things are somewhat ok, but I'm perplexed regarding the results from svm_predict. One dumb question: I presume the right way to feed data into libsvm (using its data file reading capabilities) is to manually subset the data as well as to prep it for libsvm format. Is this correct? When processing 2 vs 8, for example, I'll generate a +1 for "2" data, a 1 for "8" data and then discard the rest. Is this the right approach? 
#24




Re: on the right track?
Hmm  running commandline versions of libsvm are corroborating numbers posted by others. I suspect the (mjohnson) .NET version has problems.

#25




Re: on the right track?
Quote:
Since several alternative interfaces to LIBSVM have got similar results (I used the R interface through the e1071 package myself), you might consider trying a different interface, if there is one that you could use in limited time. Other than that, the combination of right looking support vector count and wrong looking errors (behaving spectacularly different in the two test runs) is difficult to explain by something you have done. 
#26




Re: on the right track?
I'm getting two possible cases (answers) for Q5. Randomisation did not help. Anyone have the same problem?
Not sure if there are any parameters to be tweaked that could help separate the cases... 
#27




Re: on the right track?
Was able to verify my numbers thanks to the original post. Got exactly the same results using libsvm with octave

#28




Re: on the right track?
Quote:
[EDIT: checking posts on the previous page, around #17, might also be helpful] Last edited by Elroch; 05282013 at 09:26 AM. Reason: Suggestion 
#29




Re: on the right track?
Thanks for the hint!

#30




Re: on the right track?
so just what I thought: it boils down to interpreting "decreasing" as "strictly decreasing". C'mon, isn't that silly now

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