Examples with "root node to leaf nodes" and their translation in Chinees
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The node searching method then includes a process of searching descendent nodes to perform a traversing from a root node to leaf nodes according to a tree index data structure (S320).
The present disclosure relates to a node search using a tree index; and, more particularly, to a method and apparatus for searching nodes by traversing the nodes from a root node to leaf nodes according to a tree index data structure.
For example, nodes are searched from a root node to leaf nodes in a process of traversing a B-tree index, whereas, when an index split occurs, the split may spread from a leaf node to a parent node, resulting in a dead lock.
This depth will increase slowly as elements are added to the tree, but an increase in the overall depth is infrequent, and results in all leaf nodes being one more node farther away from the root.
Hierarchical softmax uses a binary tree and constructs the loss function based on the path from the root node to the leaf node. The gradient computational overhead for each step in the training process is related to the logarithm of the dictionary size.
Searching is quite similar to searching in a B+ tree. The search starts from the root node of the tree. Every internal node contains a set of rectangles and pointers to the corresponding child node and every leaf node contains the rectangles of spatial objects (the pointer to some spatial object can be there).
Since each node stores the intervals that overlap it, with all intervals completely to the left of its center point in the left subtree, similarly for the right subtree, it follows that each interval is stored in the node closest to the root from the set of nodes whose center point it overlaps. Normal deletion operations in a binary tree (for the case where the node being deleted has two children) involve promoting a node further from the leaf to the position of the node being deleted (usually the leftmost child of the right subtree, or the rightmost child of the left subtree). Deleting a node with two children from a binary search tree using the in-order predecessor (rightmost node in the left subtree, labelled 6).
Each round of Monte Carlo tree search consists of four steps: Selection: start from root R and select successive child nodes until a leaf node L is reached.
In this kind of scenario, the consolidation management structure need only use the parent Group as the root node. Other participating Business Units are leaf nodes, as shown in the figure below
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