boost 1.59 VS 2015

[skn123]

grassmann_pca.hpp(687): error C2780: 'boost::_bi::bind_t<_bi::dm_result<MT::* ,A1>::type,boost::_mfi::dm<M,T>,_bi::list_av_1::type> boost::bind(M T::* ,A1)': expects 2 arguments - 3 provided
E:\ThirdPartyLibraries_VS2015\64Bit\boost-1_59\include\boost-1_59\boost/bind/bind.hpp(2018): note: see declaration of 'boost::bind'
G:\Work_Dump\Integrated_Pipeline\src\Utilities\DimensionalityReduction\Linear\PCA\GrassmannPCA\GrassmannPCA.cpp(93): note: see reference to function template instantiation 'bool grassmann_averages_pca::grassmann_pca<data_t,grassmann_averages_pca::details::norm2>::batch_process<grassmann_averages_pca::details::ublas_helpers::row_iter,grassmann_averages_pca::details::ublas_helpers::row_iter<output_matrix_t>>(const size_t,size_t,const it_t,const it_t,it_o_basisvectors_t,const std::vector<data_t,std::allocator<_Ty>> *)' being compiled
with
[
it_t=grassmann_averages_pca::details::ublas_helpers::row_iter,
it_o_basisvectors_t=grassmann_averages_pca::details::ublas_helpers::row_iter<output_matrix_t>,
data_t=data_t,
_Ty=data_t
]

[raffienficiaud]

Hi,

Thank you for the feedback, would you please test the develop branch? I fixed the Matlab compilation issue, the unit test are still failing the compilation though.

Thanks,

[skn123]

I don't use MATLAB. Do you have any example for out-of-sample projection? I can test it then with my own data.

[skn123]

An update; If I use this module within my own data; I get "plausible" results if I do not do centering of data. However, the results are garbage if data centering takes place.

[raffienficiaud]

What do you mean by "out-of-sample" ? There are direct use of the algorithms in the "application" folder that you may use.

When you say "garbage", do you think this is buggy or that the method is not adapted? What kind of data are you trying to project?

[skn123]

First point:
https://github.com/casperkaae/MATLAB/blob/master/drtoolbox/out_of_sample.m

This is what I mean by OOS

I am using spectral data; The code by itself is not buggy. However, I have checked that if I do not "center the data" before calling your routine, then it works fine. However, if I do apply the centering and use the formula listed in the link above, then the results are garbage.

However, it may so happen that the formula shown in the code is not applicable for your method. So, if you have anything else that would achieve OOS then please share an example of that.