SuperNN
1.0.0
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Public Attributes | |
Eigen::VectorXd | gradient |
Error gradient matrix. More... | |
Eigen::MatrixXd | hessian |
Quasi-Hessian matrix. More... | |
Eigen::VectorXd | t_jacob_line |
Transposed Jacobian line. More... | |
Eigen::VectorXd | weights |
Weight matrix (same as the network weights, but in a suitable format to the algorithm. More... | |
Eigen::VectorXd | weights_backup |
Backup of the weights, for backtracking. More... | |
Definition at line 385 of file training.cpp.
Eigen::VectorXd SuperNN::NBN::Hist::gradient |
Error gradient matrix.
Definition at line 394 of file training.cpp.
Eigen::MatrixXd SuperNN::NBN::Hist::hessian |
Quasi-Hessian matrix.
Definition at line 388 of file training.cpp.
Eigen::VectorXd SuperNN::NBN::Hist::t_jacob_line |
Transposed Jacobian line.
Definition at line 391 of file training.cpp.
Eigen::VectorXd SuperNN::NBN::Hist::weights |
Weight matrix (same as the network weights, but in a suitable format to the algorithm.
Definition at line 398 of file training.cpp.
Eigen::VectorXd SuperNN::NBN::Hist::weights_backup |
Backup of the weights, for backtracking.
Definition at line 401 of file training.cpp.