[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 rcurtin):

 Wow, I didn't think it would be that drastic of a performance gain; good
 to hear though.

 When you're done with the test, can you adapt it to use the Boost Unit
 Test Framework format?  See `src/mlpack/tests/` for examples.  The key is
 just that you're using `BOOST_AUTO_TEST_CASE()` and
 `BOOST_AUTO_TEST_SUITE()` instead of defining `main()`, and instead of
 `assert()` you're using `BOOST_REQUIRE_CLOSE()` or `BOOST_REQUIRE_EQUAL()`
 or `BOOST_REQUIRE_SMALL()`.

 The last thing to be done before this is ready is to create a standalone
 executable, but I'll take care of that.  Once the test is done, I'll see
 your commit, then I'll write `pca_main.cpp`.  Then, we can approach #47.
 :)

-- 
Ticket URL: <https://trac.research.cc.gatech.edu/fastlab/ticket/126#comment:13>
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MLPACK is an intuitive, fast, and scalable C++ machine learning library developed by the FASTLAB at Georgia Tech under Dr. Alex Gray.