Search - 2-3 tree

Search - 2-3 tree - List

[Mathimatics-Numerical algorithms] 2309 DL : 0: 北京大学ACM比赛题目 Consider an infinite full binary search tree (see the figure below), the numbers in the nodes are 1, 2, 3, .... In a subtree whose root node is X, we can get the minimum number in this subtree by repeating going down the left node until the last level, and we can also find the maximum number by going down the right node. Now you are given some queries as \"What are the minimum and maximum numbers in the subtree whose root node is X?\" Please try to find answers for there queries.
Date : 2008-10-13 Size : 13.63kb User : pengfam
[Mathimatics-Numerical algorithms] btree2 DL : 0: 用C++实现的B-Tree算法- B-Tree algorithm realizes which with C
Date : 2026-01-03 Size : 1kb User : 站长
[Mathimatics-Numerical algorithms] 克鲁斯卡尔(Kruskal)算法 DL : 0: 克鲁斯卡尔(Kruskal)算法（1）算法思想（2）算法特点（3）Kruskal算法的抽象描述（4）用Kruskal算法构造最小生成树的过程（5）算法分析- Kruse Cull (Kruskal) the algorithm (1) the algorithm thought (2) the algorithm characteristic (3) the Kruskal algorithm abstract description (4) slightly produces tree s process with the Kruskal algorithm structure (5) the algorithmic analysis
Date : 2026-01-03 Size : 1kb User : 王猛
[Mathimatics-Numerical algorithms] treebintree DL : 0: （1）输入字符序列，建立二叉链表。（2）中序遍历二叉树:递归算法。（3）中序遍历二叉树:非递归算法（最好也能实现先序，后序非递归算法）。（4）求二叉树的高度。（5）求二叉树的叶子个数。（6）建立中序线索二叉树，并实现中序遍历。（8）借助队列实现二叉树的层次遍历。（9）在主函数中设计一个简单的菜单，分别调试上述算法。 -(1) input sequence of characters, the establishment of binary list. (2) traversal of binary tree: recursive algorithm. (3) in order binary tree traversal: Non-recursive algorithm (the best can achieve the first order, after the sequence of non-recursive algorithm). (4) for tree height. (5) for the number of tree leaves. (6) in order to establish clues to binary tree and traversal implementation. (8) through the queue to achieve the level of binary tree traversal. (9) in the main function in the design of a simple menu, respectively, the above algorithm debugging.
Date : 2026-01-03 Size : 315kb User : jack
[Mathimatics-Numerical algorithms] 2309 DL : 0: 北京大学ACM比赛题目 Consider an infinite full binary search tree (see the figure below), the numbers in the nodes are 1, 2, 3, .... In a subtree whose root node is X, we can get the minimum number in this subtree by repeating going down the left node until the last level, and we can also find the maximum number by going down the right node. Now you are given some queries as "What are the minimum and maximum numbers in the subtree whose root node is X?" Please try to find answers for there queries. -Peking University ACM competitions topics Consider an infinite full binary search tree (see the figure below), the numbers in the nodes are 1, 2, 3, .... In a subtree whose root node is X, we can get the minimum number in this subtree by repeating going down the left node until the last level, and we can also find the maximum number by going down the right node. Now you are given some queries as
Date : 2026-01-03 Size : 13kb User : pengfam
[Mathimatics-Numerical algorithms] automatic-classification-cluster DL : 0: 一、问题描述若要在n个城市之间建役通信网络，只福要架设n-1条级路即可．如何以最低的经济代价建设这个通信网，是一个网的最小生成树问题。二、基本要求（1）利用克鲁斯卡尔算法求图的最小生成树。（2）能实现教科书6.5节中定义的抽象数据类型MFSet.以此表示构造生成树过程中的连通分量。 (3 ) 以文本形式输出生成树中各条边以及他们的权值．三、需求分析 1、构造图结构。 2、利用克鲁斯卡尔算法求图的最小生成树。 3、完成生成树的输出。 -I. Description of the problem to the n cities built between the service communication networks, Fuk only n-1 to set up the way to class Article. How to minimize the economic cost of building the communications network is a network of minimum spanning tree problem. Second, the basic requirements of (1) the use of Kruskal Algorithm for Minimum Spanning Tree. (2) to achieve 6.5 in the textbook definition of abstract data types MFSet. Spanning tree structure as that in the process of component connectivity. (3) to output text in the spanning tree edges and their weights. Third, a needs analysis, structural map structure. 2, the use of Kruskal Algorithm for Minimum Spanning Tree. 3, complete the spanning tree output.
Date : 2026-01-03 Size : 668kb User : 赵婧
[Mathimatics-Numerical algorithms] 15-4 DL : 0: Example 编译：mpicc mst.c mst 运行：本实例中使用了5个处理器。 mpirun –np 5 mst 运行结果： Input the size of matrix:9 0 4 5 8 6 2 5 7 3 5 0 8 3 1 6 4 9 5 7 2 0 6 4 1 3 8 9 4 5 6 0 5 7 2 1 6 4 5 8 7 0 2 3 4 7 4 1 4 7 5 0 7 8 4 7 8 9 3 2 1 0 6 7 4 2 1 4 3 5 8 0 9 5 3 2 8 9 7 6 2 0 最终输出结果： the MST is: 0 0 0 0 0 2 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 1 0 1 2 0 0 0 0 0 0 0 1 0 0 1 0 0 0 2 0 0 0 2 1 1 0 2 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 2 0 0 0 0 0 0 说明：输出结果为最小生成树的边。 - Example Compile: mpicc mst.c mst Run: The example of the use of the five processors. mpirun-np 5 mst Run Results: Input the size of matrix: 9 045,862,573 508,316,495 720,641,389 456,057,216 458,702,347 414,750,784 789,321,067 421,435,809 532,897,620 The final output: the MST is: 000,002,000 000,011,000 000,001,012 000,000,010 010,002,000 211,020,100 000,001,000 001,100,000 002 million Description: The output for the minimum spanning tree edges.
Date : 2026-01-03 Size : 2kb User : aaa
[Mathimatics-Numerical algorithms] tree DL : 0: 1.必须完成图的存储功能。图的输入可由命令行完成； 2.按遍历到的先后顺序依次输出G中各结点内容； 3.以文本形式输出生成树中各条边以及它们的权值。 -1. Must complete map of the storage function. Map the input command line can be completed 2. According to the order traversal order of the output G of the contents of each node 3. As text output in the spanning tree edges and their weights.
Date : 2026-01-03 Size : 4kb User : 张岩
[Mathimatics-Numerical algorithms] figtree-0.9.3 DL : 0: FIGTree is a library that provides a C/C++ and MATLAB interface for speeding up the computation of the Gauss Transform.
Date : 2026-01-03 Size : 1.17mb User : id0
[Mathimatics-Numerical algorithms] 决策树与随机森林 DL : 0: 给出对决策树与随机森林的认识。主要分析决策树的学习算法：信息增益和ID3、C4.5、CART树，然后给出随机森林。决策树中，最重要的问题有3个: 1. 特征选择。即选择哪个特征作为某个节点的分类特征； 2. 特征值的选择。即选择好特征后怎么划分子树； 3. 决策树出现过拟合怎么办？下面分别就以上问题对决策树给出解释。决策树往往是递归的选择最优特征，并根据该特征对训练数据进行分割。(The understanding of decision tree and random forest is given. This paper mainly analyzes the learning algorithm of decision tree: information gain and ID3, C4.5, CART tree, and then give the random forest. Among the decision trees, there are 3 of the most important issues. 1. feature selection. Which is to choose which feature as the classification of a node; 2. the selection of eigenvalues. That is, how to divide the subtrees after the selection of the good features. 3. how to do the fitting of the decision tree? The following questions are explained on the decision tree respectively. The decision tree is often the optimal feature of the recursive selection, and the training data are segmented according to the feature.)
Date : 2026-01-03 Size : 2.02mb User : ZJN27