class PCATrainer

This class is designed to compute Principal Component Analysis

Inheritance:


Public Fields

[more]int n_inputs
number of inputs
[more]Mat* CovMat
covariance matrix of the data
[more]real* Xm_
mean vector
[more]Mat* eigenvectors
eigenvectors
[more]real** eigenvectors_
eigenvectors of the PCAMachine (to be filled)
[more]Vec* eigenvalues
eigenvalues
[more]real* eigenvalues_
eigenvalues of the PCAMachine (to be filled)
[more]int verbose_level
verbosity level
[more]bool saveCovar
save the covariance matrix

Public Methods

[more] PCATrainer(PCAMachine* machine_)
[more]virtual void train(DataSet* data_, MeasurerList* measurers_ = NULL)
[more]virtual ~PCATrainer()


Documentation

This class is designed to compute Principal Component Analysis

oint n_inputs
number of inputs

oMat* CovMat
covariance matrix of the data

oreal* Xm_
mean vector

oMat* eigenvectors
eigenvectors

oreal** eigenvectors_
eigenvectors of the PCAMachine (to be filled)

oVec* eigenvalues
eigenvalues

oreal* eigenvalues_
eigenvalues of the PCAMachine (to be filled)

oint verbose_level
verbosity level

obool saveCovar
save the covariance matrix

o PCATrainer(PCAMachine* machine_)

ovirtual void train(DataSet* data_, MeasurerList* measurers_ = NULL)

ovirtual ~PCATrainer()


This class has no child classes.
Author:
Sebastien Marcel (marcel@idiap.ch) Wed 28 Jun 2006 05:19:41 PM CEST
Version:
2.0
Since:
1.0

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