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KMeanIntroduction
- 聚类分析是将集合中的数据按其相似性大小分成不同类别的一种方法,它是模式 识别中多变量无监督学习的一个分支,己成功地用于医学,地质,财务,工程,图像 处理和文档等的数据分类中；含有实现此算法的源码 -cluster analysis is to pool the data according to similar size into a different category, It is pattern recognition multivariable Unsupervised Le
dfdgg
- 图象处理源代码集 图像分割是图像处理、模式识别、计算机视觉等领域中极为重要的内容之一，是实现自动图像分析时首先需要完成的操作。它是根据图像的某些特征或特征集合的相似性准则，对图像像素进行分组聚类，把图像平面划分为一系列有意义的区域，使其后的图像分析及识别等高级处理阶段所要处理的数据量大大减少，同时又保留有关图像结构特征的信息。由于分割中出现的误差会传播至高层次处理阶段，因此分割的精确程度是至关重要的。-image processing source code is a set image s
cluster-hyper-dim
- This paper studies the problem of categorical data clustering, especially for transactional data characterized by high dimensionality and large volume. Starting from a heuristic method of increasing the height-to-width ratio of the cluster hist
hadoop
- Hadoop: The Definitive Guide-Hadoop: The Definitive Guide helps you harness the power of your data. Ideal for processing large datasets, the Apache Hadoop framework is an open source implementation of the MapReduce algorithm on which Google built its
File10
- Web文档聚类系统的设计与实现：数据挖掘；聚类分柝：文本挖掘；预处理；聚类组合；可 视化；欧氏距离-Web Document Clustering Design and Implementation: Data mining Clustering Hierarchical: text mining pretreatment cluster combinations visualization Euclidean distance
mohuchuli
- 模糊C均值聚类算法的步骤还是比较简单的，模糊C均值聚类（FCM），即众所周知的模糊ISODATA，是用隶属度确定每个数据点属于某个聚类的程度的一种聚类算法。-Fuzzy c-means clustering algorithm steps it is quite simple, fuzzy c-means clustering (FCM), known as fuzzy membership ISODATA, it is to use to make sure that each data po
An-Introduction-to-Parallel-and-Vector-Scientific
- In this text, students of applied mathematics, science and engineering are introduced to fundamental ways of thinking about the broad context of parallelism. The authors begin by giving the reader a deeper understanding of the issues through a genera
SQL-Server-Cluster-Research
- 本文主要讨论了计算机集群系统地高可用性、高性能和可扩展性。通过分析现有数 据库体系的不足，利用计算机集群的高可用性，创建高可用性数据库集群，为用户提供 有力的数据保障，使其具有良好的故障转移、可扩展性、数据一致性的功能。-This article focuses on the compmer cluster system to high—availability,high performance and scalability by analyzing the existing da
Multivariate-Data-Analysis-Using-Spss(17)
- A Guide to Multivariate Techniques Preparation for Statistical Analysis Review: ANOVA Review: ANCOVA MANOVA MANCOVA Repeated Measure Analysis Factor Analysis Discriminant Analysis Cluster Analysis
Symantec-big-cluster-program
- 双机群集系统中节点的距离较远，一般位于不同的城市，异地之间的节点进行数据备份，以实现系统的容灾功能。-Far distance of the node in the two-machine cluster system, usually located in different cities, the nodes between the off-site data backup, system disaster recovery functions.
cluster-analysis
- 进行模糊C均值聚类,读取数据，并进行标准化变换-Fuzzy C-means clustering, data is read and converted to standardize
Load-Balancing
- WEB服务器集群系统中负载平衡的设计与实现 -With the increase of users and dense tasks in Internet and Intranet, the transacting capability of the single Web server is limited, which has already become the new bottleneck of network visiting. If the Web server clust
ostu
- 最大类间方差的基本思想是使用一个阈值将整个数据分成两个类，假如两个类之间的方差最大，那么这个阈值就是最佳的阈值-The between-cluster variance as the basic idea is to use a threshold to the whole data is divided into two classes, if the maximum variance between two classes, then the threshold value is the b
MonTestRandom
- k-means is one of the simplest unsupervised learning algorithms that solve the well known clustering problem. The procedure follows a simple and easy way to classify a given data set through a certain number of clusters (assume k clusters) fixed apri
Clustering-Algorithms-Research
- 对近年来聚类算法的研究现状与新进展进行归纳总结.一方面对近年来提出的较有代表性的聚类算法,从算法思想、关键技术和优缺点等方面进行分析概括 另一方面选择一些典型的聚类算法和一些知名的数据集,主要从正确率和运行效率两个方面进行模拟实验,并分别就同一种聚类算法、不同的数据集以及同一个数据集、不同的聚类算法的聚类情况进行对比分析.最后通过综合上述两方面信息给出聚类分析的研究热点、难点、不足和有待解决的一些问题.上述工作将为聚类分析和数据挖掘等研究提供有益的参考.-Status and Progress
Multi-Agent-Based-IDS-for-WSN
- 本文提出一种无线传感器网络入侵检测解决方案针对分簇式无线传感器网络的特点, 通过让节点和簇头分别执行不同检测任务, 结合本地检测和联合检测, 并采用多个代理模块分别实现数据收集、分析检测和入侵响应和代理管理的任务,是一套完整的IDS体系。-This paper proposes a wireless sensor network intrusion detection characteristics solutions cluster wireless sensor network, data