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Diffstat (limited to 'include/gensvm.h')
| -rw-r--r-- | include/gensvm.h | 105 |
1 files changed, 0 insertions, 105 deletions
diff --git a/include/gensvm.h b/include/gensvm.h deleted file mode 100644 index 24708bc..0000000 --- a/include/gensvm.h +++ /dev/null @@ -1,105 +0,0 @@ -/** - * @file gensvm.h - * @author Gertjan van den Burg - * @date August, 2013 - * @brief Definitions for common structures - * - * @details - * Contains documentation and declarations of GenModel and GenData. - * - */ - -#ifndef GENSVM_H -#define GENSVM_H - -#include "types.h" - -/** - * @brief A structure to represent a single GenSVM model. - * - */ -struct GenModel { - int weight_idx; - ///< which weights to use (1 = unit, 2 = group) - long K; - ///< number of classes in the dataset - long n; - ///< number of instances in the dataset - long m; - ///< number of predictor variables in the dataset - double epsilon; - ///< stopping criterion for the IM algorithm. - double p; - ///< parameter for the L-p norm in the loss function - double kappa; - ///< parameter for the Huber hinge function - double lambda; - ///< regularization parameter in the loss function - double *W; - ///< weight matrix - double *t; - ///< translation vector - double *V; - ///< augmented weight matrix - double *Vbar; - ///< augmented weight matrix from the previous iteration of the IM - ///< algorithm - double *U; - ///< simplex matrix - double *UU; - ///< 3D simplex difference matrix - double *Q; - ///< error matrix - double *H; - ///< Huber weighted error matrix - double *R; - ///< 0-1 auixiliary matrix, this matrix is n x K, with for row i a 0 on - ///< column y[i]-1, and 1 everywhere else. - double *rho; - ///< vector of instance weights - double training_error; - ///< loss function value after training has finished - char *data_file; - ///< filename of the data - KernelType kerneltype; - ///< type of kernel used in the model - double *kernelparam; - ///< array of kernel parameters, size depends on kernel type -}; - -/** - * @brief A structure to represent the data. - * - * @param K number of classes - * @param n number of instances - * @param m number of predictors - * @param *y pointer to vector of class labels - * @param *Z pointer to augmented data matrix - * @param *RAW pointer to augmented raw data matrix - * @param *J pointer to regularization vector - * @param kerneltype kerneltype used in GenData::Z - * @param *kernelparam kernel parameters used in GenData::Z - * - */ -struct GenData { - long K; - ///< number of classes - long n; - ///< number of instances - long m; - ///< number of predictors (width of RAW) - long r; - ///< number of eigenvalues (width of Z) - long *y; - ///< array of class labels, 1..K - double *Z; - ///< augmented data matrix (either equal to RAW or to the eigenvectors - ///< of the kernel matrix) - double *RAW; - ///< augmented raw data matrix - double *Sigma; - KernelType kerneltype; - double *kernelparam; -}; - -#endif |
