diff options
Diffstat (limited to 'src/gensvm_optimize.c')
| -rw-r--r-- | src/gensvm_optimize.c | 25 |
1 files changed, 16 insertions, 9 deletions
diff --git a/src/gensvm_optimize.c b/src/gensvm_optimize.c index 4f13f50..277f503 100644 --- a/src/gensvm_optimize.c +++ b/src/gensvm_optimize.c @@ -185,12 +185,12 @@ double gensvm_get_loss(struct GenModel *model, struct GenData *data, * diagonal matrix A with elements * @f[ * A_{i, i} = \frac{1}{n} \rho_i \sum_{j \neq k} \left[ - * \varepsilon_i a_{ijk}^{(p)} + (1 - \varepsilon_i) \omega_i + * \varepsilon_i a_{ijk}^{(1)} + (1 - \varepsilon_i) \omega_i * a_{ijk}^{(p)} \right], * @f] * where @f$ k = y_i @f$. - * Since this matrix is only used to calculate the matrix @f$ Z' A Z @f$, it is - * efficient to update a matrix ZAZ through consecutive rank 1 updates with + * Since this matrix is only used to calculate the matrix @f$ Z' A Z @f$, it + * is efficient to update a matrix ZAZ through consecutive rank 1 updates with * a single element of A and the corresponding row of Z. The BLAS function * dsyr is used for this. * @@ -221,7 +221,8 @@ double gensvm_get_loss(struct GenModel *model, struct GenData *data, * * @param [in,out] model model to be updated * @param [in] data data used in model - * @param [in] B pre-allocated matrix used for linear coefficients + * @param [in] B pre-allocated matrix used for linear + * coefficients * @param [in] ZAZ pre-allocated matrix used in system * @param [in] ZAZV pre-allocated matrix used in system solving * @param [in] ZAZVT pre-allocated matrix used in system solving @@ -538,7 +539,7 @@ void gensvm_get_update(struct GenModel *model, struct GenData *data, double *B, * @param[in] dataset corresponding GenData * */ -void gensvm_category_matrix(struct GenModel *model, struct GenData *dataset) +void gensvm_category_matrix(struct GenModel *model, struct GenData *data) { long i, j; long n = model->n; @@ -546,7 +547,7 @@ void gensvm_category_matrix(struct GenModel *model, struct GenData *dataset) for (i=0; i<n; i++) { for (j=0; j<K; j++) { - if (dataset->y[i] != j+1) + if (data->y[i] != j+1) matrix_set(model->R, K, i, j, 1.0); else matrix_set(model->R, K, i, j, 0.0); @@ -564,6 +565,9 @@ void gensvm_category_matrix(struct GenModel *model, struct GenData *dataset) * other rows of the simplex matrix are calculated. These difference vectors * are stored in a matrix, which is one horizontal slice of the 3D matrix. * + * We use the indices i, j, k for the three dimensions n, K-1, K of UU. Then + * the i,j,k -th element of UU is equal to U(y[i]-1, j) - U(k, j). + * * @param[in,out] model the corresponding GenModel * @param[in] data the corresponding GenData * @@ -579,7 +583,8 @@ void gensvm_simplex_diff(struct GenModel *model, struct GenData *data) for (i=0; i<n; i++) { for (j=0; j<K-1; j++) { for (k=0; k<K; k++) { - value = matrix_get(model->U, K-1, data->y[i]-1, j); + value = matrix_get(model->U, K-1, + data->y[i]-1, j); value -= matrix_get(model->U, K-1, k, j); matrix3_set(model->UU, K-1, K, i, j, k, value); } @@ -624,8 +629,10 @@ void gensvm_step_doubling(struct GenModel *model) * @f[ * h(q) = * \begin{dcases} - * 1 - q - \frac{\kappa + 1}{2} & \text{if } q \leq -\kappa \\ - * \frac{1}{2(\kappa + 1)} ( 1 - q)^2 & \text{if } q \in (-\kappa, 1] \\ + * 1 - q - \frac{\kappa + 1}{2} & \text{if } q \leq + * -\kappa \\ + * \frac{1}{2(\kappa + 1)} ( 1 - q)^2 & \text{if } q \in + * (-\kappa, 1] \\ * 0 & \text{if } q > 1 * \end{dcases} * @f] |