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Re: on the right track?
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Re: on the right track?
I got exactly the same figures as the original poster. I'm using libsvm with the C programming language.
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Re: on the right track?
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For the previous week's homework, I looked for alpha greater than ![]() Since we're all getting basically the same numbers, I have more confidence that I'm doing it right. |
Re: on the right track?
Thanks Sendai, That was a good idea.
I'm using scikit-learn too, a pretty nice python module. Your results helped me to figure out that I needed to set the parameters gamma and coef0 in sklearn.svm.SVC(...) to 1. These parameters don't appear in the lecture. Now I've got the same results. |
Re: on the right track?
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Re: on the right track?
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Re: on the right track?
I'm trying libsvm through C, with following parameters:
param.svm_type = C_SVC; param.kernel_type = POLY; param.degree = 2; param.gamma = 1; param.coef0 = 1; param.nu = 0.5; param.cache_size = 200; param.C = 0.01; param.eps = 1e-3; param.p = 0.1; param.shrinking = 1; param.probability = 0; param.nr_weight = 0; param.weight_label = NULL; param.weight = NULL; but getting Ein as 0.350 with 0 versus 7 classification. Also unable to find good explaination of these parameters anywhere. Any help? Thanks in advance. |
Re: on the right track?
I found the issue...thanks for reply from buttterscotch. The problem was with the way I was initializing 'svm_node' structure after reading the training data.
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Re: on the right track?
Seems good to me. Are you getting the same number of support vectors with Sendai's post? You might want to verify how you calculate the error. The sv_coefficients are not just "alpha", but "y*alpha"
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