[mlpack-svn] [MLPACK] #126: Implement simple PCA

[MLPACK Trac]

#126: Implement simple PCA
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  Reporter:  rcurtin                           |        Owner:  ajinkya   
      Type:  wishlist                          |       Status:  assigned  
  Priority:  major                             |    Milestone:  MLPACK 1.0
 Component:  MLPACK                            |   Resolution:            
  Keywords:  pca kernel_pca covariance method  |     Blocking:  47        
Blocked By:                                    |  
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Comment (by ajinkya):

 should we have corresponding wrapper implementations for all these pca
 methods from armadillo ?
 mat coeff = princomp(mat X)
 cx_mat coeff = princomp(cx_mat X)

 princomp(mat coeff, mat X)
 princomp(cx_mat coeff, cx_mat X)

 princomp(mat coeff, mat score, mat X)
 princomp(cx_mat coeff, cx_mat score, cx_mat X)

 princomp(mat coeff, mat score, vec latent, mat X)
 princomp(cx_mat coeff, cx_mat score, vec latent, cx_mat X)

 princomp(mat coeff, mat score, vec latent, vec tsquared, mat X)
 princomp(cx_mat coeff, cx_mat score, vec latent, cx_vec tsquared, cx_mat
 X)

 I am done writing the test case. If we want all the above cases to be
 handled, then should the test case test all the apis ??

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Ticket URL: <https://trac.research.cc.gatech.edu/fastlab/ticket/126#comment:4>
MLPACK <www.fast-lab.org>
MLPACK is an intuitive, fast, and scalable C++ machine learning library developed by the FASTLAB at Georgia Tech under Dr. Alex Gray.