Examples with "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).
节点搜索方法还包括搜索后继节点,以根据树形索引数据结构从根节点到叶节点进行遍历的过程(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.
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.
In a decision tree, all paths from the root node to the leaf node proceed by way of conjunction, or AND.
决策图 [ 编辑 ] 在决策树中, 从根节点到叶节点的路径采用汇合或与 。
Internal nodes Internal nodes are all nodes except for leaf nodes and the root node.
内部节点 内部节点是除叶子节点和根节点之外的所有节点。
The tree index data structure includes a directory node having a descendent node and a leaf node without having a descendent node.
树形索引数据结构包括具有后继节点的目录节点和没有后继节点的叶节点。
the following graph shows a selected cluster that contains leaf nodes and a node that is the root of a sub-tree
下图显示了一个选定群集,该群集包含叶节点和一个作为子树的根的节点
Some balanced trees store values only at leaf nodes, and use different kinds of nodes for leaf nodes and internal nodes.
一些平衡树只在叶子节点中存储值,而且叶子节点和内部节点使用不同的结构。
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 SQL Server indexes, an intermediate index node that points to other intermediate nodes or leaf nodes.
SQL Server 索引中指向其他中间节点或叶节点的中间索引节点。
A catalog file is ordered as a B-tree which consists of a header node, leaf node, map node and index node and the allocated block numbers of the files are stored in MDB.
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).
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