/usr/include/pca.h is in libalglib-dev 2.6.0-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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Copyright (c) 2008, Sergey Bochkanov (ALGLIB project).
>>> SOURCE LICENSE >>>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation (www.fsf.org); either version 2 of the
License, or (at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
A copy of the GNU General Public License is available at
http://www.fsf.org/licensing/licenses
>>> END OF LICENSE >>>
*************************************************************************/
#ifndef _pca_h
#define _pca_h
#include "ap.h"
#include "ialglib.h"
#include "hblas.h"
#include "reflections.h"
#include "creflections.h"
#include "sblas.h"
#include "ablasf.h"
#include "ablas.h"
#include "ortfac.h"
#include "blas.h"
#include "rotations.h"
#include "bdsvd.h"
#include "svd.h"
#include "descriptivestatistics.h"
/*************************************************************************
Principal components analysis
Subroutine builds orthogonal basis where first axis corresponds to
direction with maximum variance, second axis maximizes variance in subspace
orthogonal to first axis and so on.
It should be noted that, unlike LDA, PCA does not use class labels.
INPUT PARAMETERS:
X - dataset, array[0..NPoints-1,0..NVars-1].
matrix contains ONLY INDEPENDENT VARIABLES.
NPoints - dataset size, NPoints>=0
NVars - number of independent variables, NVars>=1
ÂÛÕÎÄÍÛÅ ÏÀÐÀÌÅÒÐÛ:
Info - return code:
* -4, if SVD subroutine haven't converged
* -1, if wrong parameters has been passed (NPoints<0,
NVars<1)
* 1, if task is solved
S2 - array[0..NVars-1]. variance values corresponding
to basis vectors.
V - array[0..NVars-1,0..NVars-1]
matrix, whose columns store basis vectors.
-- ALGLIB --
Copyright 25.08.2008 by Bochkanov Sergey
*************************************************************************/
void pcabuildbasis(const ap::real_2d_array& x,
int npoints,
int nvars,
int& info,
ap::real_1d_array& s2,
ap::real_2d_array& v);
#endif
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