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http://www.di.unipi.it/~gulli/coding/pca_eigen.zip is correct path to the archive, didn't it?
yes, and the archive should be complete now.
Hi, I was searching around on PCA snippet/library in C++ for weeks, and I found it here it seems like the codes I needed, do you have any documentation or any quick guides on how to use it? I'm new.. Thanks a lot and appreciate your helps.. >.<
yes..im also need PCA code..for this year i decide to use PCA as my technique to predict the aging face...but i am not understand if in c++..could this source code of PCA in java???anyone can help me...
Dear Antonio,I really appreciate your code on PCA. It is really helpful. There is one section of the code I don't understand. This is the "// sort and get the permutation indices" section. Is this where you try to get the largest eigen value? And how do I pair up each eigen value with its corresponding eigen vector?The out put for this section looks like this:eigen=1.62753 pi=3eigen=3.94939 pi=1eigen=8.96768 pi=2eigen=18.5922 pi=0Thanks a lot.
Hi thanks a lot. It's very helpful! you know how to convert these MatrixXd VectorXd to Python without using Boost or swig?Thanks!!
Thanks for the code. I prefer a much simpler solution to implement this as posted here:http://forum.kde.org/viewtopic.php?f=74&t=110265Works very well and is much shorter.
Hi, I think your implementation is wrong, instead of calculating mean of point coordinate, mean of each dimension should be calculated. The mean vector should have a length same as the number of dimension
Nice work. but could you direct us to the other libraries used in the code?