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made code faster

This commit is contained in:
Davis King 2016-04-26 09:52:19 -04:00
parent 47fbaff093
commit 69a12074a2
1 changed files with 11 additions and 5 deletions
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16
dlib/optimization/elastic_net.h
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@ -32,14 +32,15 @@ namespace dlib
// rows then we can get rid of them by doing some SVD magic. Doing this doesn't
// make the final results of anything change but makes all the matrices have
// dimensions that are X.nr() in size, which can be much smaller.
matrix<double> XX;
XX = X_*trans(X_);
matrix<double,0,1> s;
svd3(trans(X_),u,s,eig_vects);
svd3(XX,u,eig_vals,eig_vects);
s = sqrt(eig_vals);
X = eig_vects*diagm(s);
u = trans(X_)*tmp(eig_vects*inv(diagm(s)));
// Later on, we will use the eigenvalues of X*trans(X) to compute the solution
// without lasso. So we save them here.
eig_vals = squared(s);
samples.resize(X.nr()*2);
@ -103,8 +104,13 @@ namespace dlib
<< " \n\t this: " << this
);
ynorm = length_squared(Y_);
Y = trans(u)*Y_;
// We can use the ynorm after it has been projected because the only place Y
// appears in the algorithm is in terms of dot products with w and x vectors.
// But those vectors are always in the span of X and therefore we only see the
// part of the norm of Y that is in the span of X (and hence u since u and X
// have the same span by construction)
ynorm = length_squared(Y);
xdoty = X*Y;
eig_vects_xdoty = trans(eig_vects)*xdoty;