PLearn 0.1
Classes | Namespaces | Functions
GenMat.h File Reference
#include <plearn/math/TMat_maths.h>
#include <plearn/math/random.h>
#include <plearn/math/parpack.h>
Include dependency graph for GenMat.h:

Go to the source code of this file.

Classes

class  PLearn::SquaredSymmMatT< MatT >
class  PLearn::ReverseMatT< MatT >
class  PLearn::MatTPlusSumSquaredVec< MatT >

Namespaces

namespace  PLearn
 

< for swap


Functions

template<class MatT >
bool PLearn::SolveLinearSymmSystemByCG (MatT A, Vec x, const Vec &b, int &max_iter, real &tol, real lambda)
 for debugging
template<class MatT >
real PLearn::PowerIteration (MatT &A, Vec x0, int &n_iterations, real RayleighQuotientTolerance, Mat final_vectors, int &final_offset)
 do it with templates
int PLearn::GramSchmidtOrthogonalization (Mat A, real tolerance=1e-6)
template<class MatT >
real PLearn::PowerIteration (MatT A, Vec x0, int &n_iterations, real RayleighQuotientTolerance, Mat final_vectors, int &final_offset, bool verbose=false)
template<class MatT >
real PLearn::InversePowerIteration (MatT A, Vec x0, int &n_iterations, int max_n_cg_iter, real RTolerance, Mat final_vectors, int &final_offset, real regularizer, bool verbose=false)
template<class MatT >
real PLearn::findSmallestEigenPairOfSymmMat (MatT &A, Vec x, real error_tolerance=1e-3, real improvement_tolerance=1e-4, int max_n_cg_iter=0, int max_n_power_iter=0, bool verbose=false)
template<class MatT >
int PLearn::SymmMatNullSpaceByInversePowerIteration (MatT &A, Mat solutions, Vec normsAx, Vec xAx, real error_tolerance=1e-3, real improvement_tolerance=1e-4, int max_n_cg_iter=0, int max_n_power_iter=0, bool verbose=false)
template<class MatT >
int PLearn::GDFindSmallEigenPairs (MatT &A, Mat X, bool diagonalize_in_the_end=true, real tolerance=1e-6, int n_epochs=0, real learning_rate=0, int normalize_every=0, real decrease_factor=0, bool verbose=false)
template<class MatT >
int PLearn::kernelPCAfromDotProducts (MatT &dot_products, Mat embedding, int max_n_eigen_iter=300, real ncv2nev_ratio=1.5, Vec *eval=0, Mat *evec=0)
template<class MatT >
int PLearn::metricMultiDimensionalScaling (MatT &square_distances, Mat embedding, int max_n_eigen_iter=300)

Detailed Description

Definition in file GenMat.h.

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