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kmeans
- 加强了的K-MEANS聚类函数,速度比以前快5 。适合多种聚类场合。一般聚类数为2-5之间为最佳。-The enhanced K-MEANS clustering function, speed 5 faster than before. Clustering for a variety of occasions. General the number of clusters for the best between 2-5.
2354125134543546
- Dijkstra算法;K-means聚类算法运用于数模之中方便快捷的找到结果。是 数模中常用的方法。-Dijkstra algorithm K-means clustering algorithm applied to digital-analog into convenient results found. Mathematical modeling is commonly used methods.
k_means
- 简单易懂的k-means聚类算法,可运行!有详细注释说明。-Straightforward k-means clustering algorithm, run! Detailed explanatory notes.
julei
- 1 掌握不同的聚类方法—基于层次与基于划分的方法 2 学会层次聚类的单连接算法 3 学会K-means算法 -A master of different clustering methods- based on hierarchical partitioning method based on hierarchical clustering 2 Society 3 Society of single-link algorithm K-means algorithm
A_Tutorial_on_Spectral_Clustering
- 谱聚类的最新英文教程,详细描述了谱聚类的每一个步骤,讲解清晰明了,想现在最实用最全面的谱聚类基础教程。-In recent years, spectral clustering has become one of the most popular modern clustering algorithms. It is simple to implement, can be solved eciently by standard linear algebra software, and
kMeansCluster
- K-Means聚类算法 Matlab代码-K-Means clustering algorithm Matlab code
kmean
- k-means聚类算法的C++实现程序,简单好理解。-k-means clustering algorithm to achieve C++ program, a simple easy to understand.
TextClusteringKmeans
- 从文本文件读入文本,分词,去停顿词,然后利用kmeans进行文本聚类-Text Clustering with K means
K_means
- 很好k-means聚类,很好的matlab源码-Good k-means clustering, a good source matlab
NewK-means-clustering-algorithm
- 珍藏版,可实现,新K均值聚类算法,分为如下几个步骤: 一、初始化聚类中心 1、根据具体问题,凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。 2、用前C个样本作为初始聚类中心。 3、将全部样本随机地分成C类,计算每类的样本均值,将样本均值作为初始聚类中心。 二、初始聚类 1、按就近原则将样本归入各聚类中心所代表的类中。 2、取一样本,将其归入与其最近的聚类中心的那一类中,重新计算样本均值,更新聚类中心。然后取下一样本,
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- 基于WEKA平台的文本聚类研究与实现 文本聚类是文本挖掘领域的一个重要研究分支,是聚类方法在文本处理领域的应用。本文对基于空间向量模型的文本聚类过程做了较深入的讨论和总结,利用文本语料库,基于数据挖掘工具研究并实现了文本聚类的过程。本文首先给出了文本聚类的思想和过程,回顾了文本聚类领域的已有成果,列举了文本聚类领域在特征表示、特征提取等方面的基础研究工作。另外,本文回顾了现有的文本聚类算法,以及常用的文本聚类效果评价指标。在研究了已有成果的基础上,本文利用20 Newsgroup文本语料库,
system-of-K-Means-and-its-plus
- 实现了k-means极其改良算法,提高了聚类的精度。内附详细文字说明及源代码,配有图形界面演示。-The implementation of k-means algorithm and its plus.Improve the accuration of clustering.The document and source are both added.
k
- k均值聚类算法源码,比较经典,无解压密码-k means clustering algorithm source code, more classic, without extracting passwords
Kmeans
- K-means算法实现文本聚类,Java实现的版本-K-means algorithm for text clustering
CPPK-means
- K均值聚类首先需要确定聚成几类,然后按照迭代的方法,计算类的重心,然后按照向量和类重心的聚类重新分类,反复重复,直到分类稳定或者重心稳定。-K means clustering first need to identify clustered into several categories, and then follow the iterative method to calculate the focus of the class, and then follow the center of
KMeans
- K均值(K-Means)聚类算法,采用模板方式实现,支持不同类型样本数据。-K-Means cluster algorithm, using template to suport any data type.
K-means
- k-means均值聚类分析代码可以实现二维文件的读入,以及文件的输出,还可以根据需要选择聚类中心数-k-means clustering analysis of two-dimensional code can read the file, and document output, but also can select the number of cluster centers
K-means-althogrim
- K-Means算法的并行化研究,划分聚类的算法,K-Means算法及改进算法。并行策略,PVM系统简介。-Parallel K-Means algorithm research, by clustering algorithm, K-Means algorithm and improved algorithm. Parallel strategy, PVM Introduction.
k-means--source-code
- k-means算法,已附数据文件。其中文件第一行的3个数字分别为数据数量、数据维度和所需聚类数-k-means algorithm, is attached data files. Which documents the first line of three figures were the amount of data, data dimension and the required number of clusters
K-means
- 一种K-均值算法附有测试数据,希望给学习聚类的提供一点帮助-One kind of K-means algorithm with test data, clustering offers hope to learn a little help