68                 lower = lower + n_leaves;
 
  154         tasks_indices[t_i] = iterator->get_indices();
 
  165     return tasks_indices;
 
  176     SG_DEBUG(
"Number of blocks = %d \n", n_blocks)
 
  178     vector<task_tree_node_t> tree_nodes = vector<task_tree_node_t>();
 
  188     for (int32_t i=0; i<(int32_t)tree_nodes.size(); i++)
 
  190         ind_t[3+i*3] = tree_nodes[i].t_min_index;
 
  191         ind_t[3+i*3+1] = tree_nodes[i].t_max_index;
 
  192         ind_t[3+i*3+2] = tree_nodes[i].weight;
 
class Task used to represent tasks in multitask learning. Essentially it represent a set of feature v...
virtual int32_t get_num_tasks() const 
void collect_leaf_tasks_recursive(CTask *subtree_root_block, CList *list)
CSGObject * get_next_element()
task_tree_node_t(int32_t min, int32_t max, float64_t w)
int32_t count_leaft_tasks_recursive(CTask *subtree_root_block)
virtual SGVector< index_t > * get_tasks_indices() const 
CSGObject * get_first_element()
int32_t count_leaf_tasks_recursive(CTask *subtree_root_block)
SGVector< float64_t > get_SLEP_ind_t()
int32_t get_num_elements()
void set_root_task(CTask *root_task)
int32_t get_num_subtasks()
all of classes and functions are contained in the shogun namespace 
bool append_element(CSGObject *data)
used to represent tasks in multitask learning 
Matrix::Scalar max(Matrix m)
void collect_tree_tasks_recursive(CTask *subtree_root_block, vector< task_tree_node_t > *tree_nodes, int low)
float64_t get_weight() const 
Class List implements a doubly connected list for low-level-objects.