计算机代写|复杂网络代写complex network代考|Definitions from Physicists

Doug I. Jones

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• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

计算机代写|复杂网络代写complex network代考|Dynamics on Networks

The diversity of definitions from sociology already indicates the conceptual difficulties involved and demonstrates that the question of what a community is may not have a simple answer. To make things worse, a number of alternative definitions have been and continue to be contributed by physicists as well $[19,20]$.

Radicchi et al. [21] have introduced the notion of community in a strong sense and in a weak sense. For a subgraph $V$ of $\mathcal{G}$ to be a community in the strong sense, they require
$$k_i^{\text {in }}>k_i^{\text {out }} \quad \forall i \in V$$
i.e., the number of internal connections $k_i^{i n}$ to other members of $V$ shall be larger than the number of external connections $k_i^{\text {out }}$ to the rest of the network. Note that $k_i^{i n}+k_i^{\text {out }}=k_i$, the degree of node $i$. Relaxing this condition, for a subgraph $V$ to be a community in a weak sense they require
$$\sum_{i \in V} k_i^{i n}>\sum_{i \in V} k_i^{o u t} .$$
A paradoxical issue arising from both of these definitions is that communities in the strong or weak sense can be formed of disconnected subgraphs as long as these subgraphs also obey the definition. It should be noted, however, that this definition was initially proposed as a stop criterion for hierarchical agglomerative or divisive clustering algorithms.

计算机代写|复杂网络代写complex network代考|Algorithms for Community Detection

One may ask how it shall be possible to design a community detection algorithm without a precise definition of community. The answer is that for many networks the community structure is known from other sources and the reasoning is that any algorithm, which is good at discovering known community structures, will be good at finding unknown ones as well. A number of real world data sets have become almost standard for this purpose and will be discussed in the following chapters and later sections.

In addition to real world networks with known community structure it has become customary to compare the performance of community detection algorithms on computer-generated test networks with known communities. The standard example is the following: Given is a graph with 128 nodes, divided into 4 communities of 32 nodes each. The degree distribution is chosen to be Poissonian with an average of $\langle k\rangle=16$. The links of every node are divided into those that connect to other members of the same community and those connecting to the rest of the network, such that
$$\langle k\rangle=\left\langle k_{i n}\right\rangle+\left\langle k_{\text {out }}\right\rangle$$
Otherwise, the network is completely random. For fixed $\langle k\rangle$, recovering the built-in community structure becomes more difficult as $\left\langle k_{\text {out }}\right\rangle$ increases at the expense of $\left\langle k_{i n}\right\rangle$. It has become customary to study the performance of an algorithm as a function of $\left\langle k_{i n}\right\rangle$.

复杂网络代写

计算机代写|复杂网络代写complex network代考|Dynamics on Networks

Radicchi等人[21]从强意义和弱意义上引入了社区的概念。对于$\mathcal{G}$的子图$V$来说，要成为一个强意义上的社区，他们需要
$$k_i^{\text {in }}>k_i^{\text {out }} \quad \forall i \in V$$

$$\sum_{i \in V} k_i^{i n}>\sum_{i \in V} k_i^{o u t} .$$

计算机代写|复杂网络代写complex network代考|Algorithms for Community Detection

$$\langle k\rangle=\left\langle k_{i n}\right\rangle+\left\langle k_{\text {out }}\right\rangle$$

有限元方法代写

tatistics-lab作为专业的留学生服务机构，多年来已为美国、英国、加拿大、澳洲等留学热门地的学生提供专业的学术服务，包括但不限于Essay代写，Assignment代写，Dissertation代写，Report代写，小组作业代写，Proposal代写，Paper代写，Presentation代写，计算机作业代写，论文修改和润色，网课代做，exam代考等等。写作范围涵盖高中，本科，研究生等海外留学全阶段，辐射金融，经济学，会计学，审计学，管理学等全球99%专业科目。写作团队既有专业英语母语作者，也有海外名校硕博留学生，每位写作老师都拥有过硬的语言能力，专业的学科背景和学术写作经验。我们承诺100%原创，100%专业，100%准时，100%满意。

MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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