On 29 May 2017 at 08:27, Tiramisu Ling <saberge...@gmail.com> wrote:
> Hi, I have a question about the difference between CBinaryLabels
> and CMultilabelLabels. Why we need to make CBinaryLabels as {-1, 1} but
> CMultilabelLabels define as {0,1...num_classs-1}? What about define
> something like 'DigitalLabels' which can accept {-1, 0, 1, ...num_classes},
> or just use CBinaryLabels as {0, 1}.
>
> Because we are going to Add global fixture with binary label data(issue
> 3812 <https://github.com/shogun-toolbox/shogun/pull/3812/files>), and I
> add some code(the for loop part
> <https://github.com/shogun-toolbox/shogun/pull/3812/files#diff-9739eb22131152d61edc04fe3812921bR64>)
> to make it could work with multilclass data(comment
> <https://github.com/shogun-toolbox/shogun/pull/3812/files#r118416713>).
> But the problem is CBinaryLabels can only accept -1 or 1 but
> CMultilabelLabels have 0,1.... So I don't know how to generate two
> different labels by *one *uniform process(don't need to distinguish or
> specify which kind of label we want). And it seems like I can't cast from
> one label to another directly.
>
I think the CBinaryLabels constructor with a threshold can help you to
create them from a vector of 0s and 1s:
https://github.com/shogun-toolbox/shogun/blob/develop/src/shogun/labels/BinaryLabels.cpp#L52
For your understanding, the reason why binary labels take values on {-1, 1}
has probably to do with the fact that some binary classification algorithms
are formulated succinctly exploiting these values. For example, consider a
linear model with weight vector is w, bias b, the feature vector of data
sample i is x_i and its label l_i. Note that l_i can be either -1 or 1.
Learning could be expressed as,
find awesome w and b
subject to
for all i, (w*x_i+b)l_i >= 0
>
> Please give me some help about that. Thank you very much!
>
> Best Regards,
> MikeLing
>
>
>
