best program for graphs

The Lift Chart (lift chart) and the gain graph (gain chart) are a very useful graphical representation in evaluating the predictive capability of a model. In SPSS, a typical gain graph is as follows:in today's blog post, bloggers will discuss with you the logic of making the gain graph and how to interpret the gain and lift graphs. In the following blog post, we will use an example of a direct mail company to explain to you. Assuming that, based on

The essence of this algorithm is to constantly find the augmented road;Km the correctness of the algorithm is based on the following theorem:If the sub-graph (i,j) consisting of all the edges (a[i]+b[j]=w[i,j) in the binary graph (called Equal sub-graph) has a complete match, then this complete match is the maximum weight matching of the binary graph.This theorem is obvious. Because for any one of the binary graphs, if it is contained in an equal sub-

Two-part diagram: The two-part graph, also known as two-part graph, is a special model in graph theory. Set g= (V,e) is a graph, if vertex V can be divided into two disjoint subsets (A, b), and each edge (I,J) in the diagram is associated with two vertices I and J respectively belong to these two different vertex sets (I in A,j in B), it is said that figure G is a two-part graph. The sufficient and necessary condition for the graph G to be two points is that G has at least two vertices and that

Respect for the work of others, reproduced please indicate the source: http://blog.csdn.net/gengqiquan/article/details/65938021, this article from: "Gengqiquan blog"The leader recently felt that Ctrip's screenshot of the growth chart sharing effect is better, so we also added a, product feel to share out of the long map needs to add the company brand watermark, so we also added A; Well, the cause of the incident is this.Long graphs are generally scrol

Directory 1 Problem Description 2 Solutions 1 problem description What is the maximum weight matching problem for two-point graphs?The most powerful two-point matching problem is to give a weighted value to each side of the binary graph, select some disjoint edges, and get the maximum total weight value.2 Solutions for the explanation of this issue, refer to end reference 1: Solving this problem can be used KM algorithm. Un

?? After the basic sorting and finding algorithm is finished, it enters the chapter of the diagram. Collation data structure has been reference to the "Data structure and algorithm C # language description" This book, is Turing series, I believe students of computer learning are very appreciative of this series of books, but to this point found that two of the writing unreasonable place. The first is the set operation, a closer look will find that the code is problematic, can not be app

nodes, and the edges (u,v) are attached to nodes U and v. In the graph G, if is an edge in E (G), then the node U is said to be adjacent to Node V, node V is adjacent to the node U, and the edge is associated with node U and Node v. The degree of Node V is the number of edges associated with it, which is recorded as TD (V).Path in Figure g= (v,e), if there is a set of edges from node VI to reach the node VJ, then the node of the node vi to the node VJ is the path f

The traversal of the graph is similar to the traversal of the tree, and we want to go through the rest of the graph from one vertex in the graph, and make each vertex accessible only once, a process called graph traversal (Traverse graph). There are generally two kinds of traversal methods of graphs, the first one is depth first search, also known as depth-first searching, referred to as DFS (Depth). The second is "breadth first traversal" (breadth f

Depth-first traversal and breadth-first traversal of graphs stored in the adjacent table, and adjacent breadth-first Traversal 1. depth-first traversal is a traversal policy for connected graphs. The basic idea is as follows: Set x to the currently accessed vertex. After marking x, select an undetected edge (x, y) starting from x ). If vertex y is found to have been accessed, re-select another side that has

} or {v1,v2,v5,v4,v7,v3,v6}The algorithm of sorting from topology shows that if the AOV network has n vertices, e edges, in the process of topological sorting, searching for vertices with zero degree, the time required to build the vertex stack is O (n). Under normal circumstances, there are n vertices to the graph, each vertex into the stack, out of the stack, output a total of n times. The operation of vertex-to-degree minus 1 is performed in total e-times. Therefore, the total time complexity

beginning and end vertices of a path are the same, the remaining vertices are not the same, it is called a simple path.⑥ Sub-chart. If there are two graphs, g= (v,e) and g1= (V1,E1), if V1 is contained in V, and E1 is contained in E, then G1 is called a sub-graph of G.⑦ connected graph and Unicom component. In undirected graph G, if there is a path from vertex v1 to vertex v2, the vertex v1 and vertex v2 are connected. If any of the two vertices in t

Definition: in an no-map, define an edge-covered point for the two endpoints of the Edge. Find a side set S contains the most edges, so that each vertex in all vertices covered by this edge set is overwritten by only one edge. The size of S is called the maximum match of the Graph.The maximal matching algorithm of the binary Graph: set the left set as a set, with the edge set as the B set. Two methods are commonly used for the maximum matching of binary grap