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.