long folds
number of folds in cross validation
double coef
coef parameter for the GenModel
double epsilon
stopping criterion for the IM algorithm.
long ID
numeric id of the task in the queue
void gensvm_task_to_model(struct GenTask *task, struct GenModel *model)
Copy parameters from GenTask to GenModel.
double p
parameter for the L-p norm in the loss function
void gensvm_free_task(struct GenTask *t)
Free the GenTask struct.
double performance
performance after cross validation
int weight_idx
which weights to use (1 = unit, 2 = group)
#define Malloc(type, size)
double gamma
gamma parameter for the GenModel
KernelType kerneltype
kerneltype parameter for the GenModel
struct GenData * test_data
pointer to the test data (if any)
A structure to represent a single GenSVM model.
struct GenTask * gensvm_copy_task(struct GenTask *t)
Deepcopy a GenTask struct.
long max_iter
maximum number of iterations of the algorithm
double degree
degree parameter for the GenModel
double lambda
lambda parameter for the GenModel
A structure for a single task in the queue.
double kappa
parameter for the Huber hinge function
long max_iter
maximum number of iterations of the algorithm
double degree
kernel parameter for poly
struct GenTask * gensvm_init_task(void)
Initialize a GenTask structure.
double kappa
kappa parameter for the GenModel
double coef
kernel parameter for poly and sigmoid
KernelType kerneltype
type of kernel used in the model
Header file for gensvm_task.c.
double gamma
kernel parameter for RBF, poly, and sigmoid
double epsilon
epsilon parameter for the GenModel
double p
p parameter for the GenModel
double lambda
regularization parameter in the loss function
struct GenData * train_data
pointer to the training data
int weight_idx
weight_idx parameter for the GenModel