搜索资源列表
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，
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
k-means
- 一个聚类的小算法。关于K-SUMMARY的，基于K-MEANS的该军-A small clustering algorithm. About K-SUMMARY-based K-MEANS of the Army
k-means
- k-means算法，用于聚类,是一种机器学习的典型算法- k-means, used to clustering
K-Means
- K-means 动态聚类算法，在人工智能、神经网络中应用非常广泛-Dynamic K-means clustering algorithm in artificial intelligence, neural network is widely used in
Exterme_k_means
- Extreme k-means，被yuboYuan提出，给定初始聚类中心，聚类快。-Extreme k-means,poposed by yuboYuan，the intial center is fixed, faster than traditional k-means
ProgramForClustering
- 分层聚类和k-means聚类代码 commandline输出-Hierarchical clustering and k-means clustering code commandline output
K-average(N-dimension)
- K均值聚类算法实现有二维的聚类扩展到任意维样本点的聚类，代码中附加了详细的原理性说明，还有相关例子提示，效果不错-K-means clustering algorithm to achieve a two-dimensional clustering extends to any dimension of the cluster sample points, the code attached to the principle of detailed instructions, and tips
K-Means-algorithm-source-program
- c++源码K-Means动态聚类算法源程序。，希望对工程应用有帮助。-K-Means dynamic clustering algorithm source program ,I hope it will be helpful.
k_means-algorithm
- k-means算法是模式识别十大算法之一 matlab仿真的k-means聚类算法-k-means algorithm for pattern recognition algorithm is one of the top ten k-means clustering algorithm
K_means
- 用于实现K-MEANS聚类分析的C++代码-Used to implement the K-MEANS clustering analysis of the C++ code