GClasses
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Computes the pseudo-inverse of a neural network. More...
#include <GNeuralNet.h>
Public Member Functions | |
GNeuralNetPseudoInverse (GNeuralNet *pNN, double padding=0.01) | |
padding specifies a margin in which label values will be clipped inside the activation function output range to avoid extreme feature values (-inf, inf, etc.). | |
~GNeuralNetPseudoInverse () | |
void | computeFeatures (const double *pLabels, double *pFeatures) |
Computes the input features from the output labels. In cases of under-constraint, the feature vector with the minimum magnitude is chosen. In cases of over-constraint, the feature vector is chosen with a corresponding label vector that minimizes sum-squared error with the specified label vector. | |
Static Public Member Functions | |
static void | test () |
Protected Attributes | |
double | m_padding |
std::vector < GNeuralNetInverseLayer * > | m_layers |
double * | m_pBuf1 |
double * | m_pBuf2 |
Computes the pseudo-inverse of a neural network.
GClasses::GNeuralNetPseudoInverse::GNeuralNetPseudoInverse | ( | GNeuralNet * | pNN, |
double | padding = 0.01 |
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) |
padding specifies a margin in which label values will be clipped inside the activation function output range to avoid extreme feature values (-inf, inf, etc.).
GClasses::GNeuralNetPseudoInverse::~GNeuralNetPseudoInverse | ( | ) |
void GClasses::GNeuralNetPseudoInverse::computeFeatures | ( | const double * | pLabels, |
double * | pFeatures | ||
) |
Computes the input features from the output labels. In cases of under-constraint, the feature vector with the minimum magnitude is chosen. In cases of over-constraint, the feature vector is chosen with a corresponding label vector that minimizes sum-squared error with the specified label vector.
static void GClasses::GNeuralNetPseudoInverse::test | ( | ) | [static] |
std::vector<GNeuralNetInverseLayer*> GClasses::GNeuralNetPseudoInverse::m_layers [protected] |
double GClasses::GNeuralNetPseudoInverse::m_padding [protected] |
double* GClasses::GNeuralNetPseudoInverse::m_pBuf1 [protected] |
double* GClasses::GNeuralNetPseudoInverse::m_pBuf2 [protected] |