Tapkee
TSNE Class Reference

#include <tsne.hpp>

Public Member Functions

void run (tapkee::DenseMatrix &X, int N, int D, ScalarType *Y, int no_dims, ScalarType perplexity, ScalarType theta)
 
void symmetrizeMatrix (int **_row_P, int **_col_P, ScalarType **_val_P, int N)
 

Private Member Functions

void computeGradient (ScalarType *, int *inp_row_P, int *inp_col_P, ScalarType *inp_val_P, ScalarType *Y, int N, int D, ScalarType *dC, ScalarType theta)
 
void computeExactGradient (ScalarType *P, ScalarType *Y, int N, int D, ScalarType *dC)
 
ScalarType evaluateError (ScalarType *P, ScalarType *Y, int N)
 
ScalarType evaluateError (int *row_P, int *col_P, ScalarType *val_P, ScalarType *Y, int N, ScalarType theta)
 
void zeroMean (ScalarType *X, int N, int D)
 
void computeGaussianPerplexity (ScalarType *X, int N, int D, ScalarType *P, ScalarType perplexity)
 
void computeGaussianPerplexity (ScalarType *X, int N, int D, int **_row_P, int **_col_P, ScalarType **_val_P, ScalarType perplexity, int K)
 
void computeGaussianPerplexity (ScalarType *X, int N, int D, int **_row_P, int **_col_P, ScalarType **_val_P, ScalarType perplexity, ScalarType threshold)
 
void computeSquaredEuclideanDistance (ScalarType *X, int N, int D, ScalarType *DD)
 

Detailed Description

Definition at line 57 of file tsne.hpp.

Member Function Documentation

◆ computeExactGradient()

void computeExactGradient ( ScalarType *  P,
ScalarType *  Y,
int  N,
int  D,
ScalarType *  dC 
)
private

Definition at line 290 of file tsne.hpp.

◆ computeGaussianPerplexity() [1/3]

void computeGaussianPerplexity ( ScalarType *  X,
int  N,
int  D,
ScalarType *  P,
ScalarType  perplexity 
)
private

Definition at line 415 of file tsne.hpp.

◆ computeGaussianPerplexity() [2/3]

void computeGaussianPerplexity ( ScalarType *  X,
int  N,
int  D,
int **  _row_P,
int **  _col_P,
ScalarType **  _val_P,
ScalarType  perplexity,
int  K 
)
private

Definition at line 482 of file tsne.hpp.

◆ computeGaussianPerplexity() [3/3]

void computeGaussianPerplexity ( ScalarType *  X,
int  N,
int  D,
int **  _row_P,
int **  _col_P,
ScalarType **  _val_P,
ScalarType  perplexity,
ScalarType  threshold 
)
private

Definition at line 579 of file tsne.hpp.

◆ computeGradient()

void computeGradient ( ScalarType *  ,
int *  inp_row_P,
int *  inp_col_P,
ScalarType *  inp_val_P,
ScalarType *  Y,
int  N,
int  D,
ScalarType *  dC,
ScalarType  theta 
)
private

Definition at line 268 of file tsne.hpp.

◆ computeSquaredEuclideanDistance()

void computeSquaredEuclideanDistance ( ScalarType *  X,
int  N,
int  D,
ScalarType *  DD 
)
private

Definition at line 742 of file tsne.hpp.

◆ evaluateError() [1/2]

ScalarType evaluateError ( ScalarType *  P,
ScalarType *  Y,
int  N 
)
private

Definition at line 330 of file tsne.hpp.

◆ evaluateError() [2/2]

ScalarType evaluateError ( int *  row_P,
int *  col_P,
ScalarType *  val_P,
ScalarType *  Y,
int  N,
ScalarType  theta 
)
private

Definition at line 365 of file tsne.hpp.

◆ run()

void run ( tapkee::DenseMatrix X,
int  N,
int  D,
ScalarType *  Y,
int  no_dims,
ScalarType  perplexity,
ScalarType  theta 
)

Definition at line 60 of file tsne.hpp.

◆ symmetrizeMatrix()

void symmetrizeMatrix ( int **  _row_P,
int **  _col_P,
ScalarType **  _val_P,
int  N 
)

Definition at line 180 of file tsne.hpp.

◆ zeroMean()

void zeroMean ( ScalarType *  X,
int  N,
int  D 
)
private

Definition at line 392 of file tsne.hpp.


The documentation for this class was generated from the following file: