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updated docs 

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Davis King 2010-12-22 00:25:53 +00:00
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@ -370,7 +370,9 @@ subject to the following constraint:
sum(alpha) == nu*y.size() sum(alpha) == nu*y.size()
0 <= min(alpha) && max(alpha) <= 1 0 <= min(alpha) && max(alpha) <= 1
trans(y)*alpha == 0 trans(y)*alpha == 0
Where f is convex. This means that Q should be symmetric and positive-semidefinite.
Where all elements of y must be equal to +1 or -1 and f is convex.
This means that Q should be symmetric and positive-semidefinite.
</pre> </pre>
<br/> <br/>
This object implements the strategy used by the LIBSVM tool. The following papers This object implements the strategy used by the LIBSVM tool. The following papers