搜索资源列表
good K-means clusters
- 这次上传的代码是关于K-means clusters的代码，希望能对大家有用。-The uploaded code is about K-means clusters.I hope it can be a help to everyone.
heartbeat-1.99.2.tar
- linux集群服务器软件代码包，已广泛应用于专业linux服务器构架中，是目前开源的集群代码中最优秀的-Linux cluster server software code. it has been widely used professional linux server architecture, which is the open-source code clusters of the best
RAC
- 在linux上单机模拟Oracle 10g RAC集群-aircraft simulated Oracle 10g RAC clusters
realDBSCAN
- 二维的DBSCAN聚类算法，输入（x,y）数组，搜索半径Eps，密度搜索参数Minpts。输出: Clusters，每一行代表一个簇，形式为簇的对象对应的原数据集的ID-two-dimensional clustering algorithm, the input (x, y) array, search radius Eps. Minpts density search parameters. Output : Clusters, each firm on behalf of a cluste
Calculatetheprobability
- calculatePXTheta---Calculate the probability of each pixel being its color conditioned on all of the clusters that were found at the previous (coarser) iteration. -calculatePXTheta -- Calculate the proba bility of each pixel being its color conditi
DBSCAN2
- DBSCAN是一个基于密度的聚类算法。改算法将具有足够高度的区域划分为簇，并可以在带有“噪声”的空间数据库中发现任意形状的聚类。-DBSCAN is a density-based clustering algorithm. Algorithm change will have enough height to the regional cluster. and to be with the "noise" of the spatial database found clus
Kmeans.Cluster.using.Guide
- 图像集群（Image Clustering） (1)图像读入，显示图像所在路径； (2)采用imgcluster函数进行图像集群，选择集群个数后进行图像集群； (3)运行后，在原图像上显示集群灰度图； (4)若要显示各个集群情况，可打开【Show Clustering Image】新窗体，显示各集群类的基于原图的彩绘区域。其中非当前集群范围，则显示灰度为255的黑色。用户可点击按纽上下查看所有集群图。-image cluster (Image Clustering) (1) re
mega32fat16
- 移植到mega32上面的fat16代码实现了，文件查找，寻找簇，文件读写等功能-transplant mega32 above fat16 code achieved, and the documents you find clusters, document literacy, and other functions
chromium_configure
- 集群计算环境下的网络通讯与负载系统，通过该软件可使集群计算机系统的负载达到最佳平衡-cluster computing environment with a network communications system load, adoption of the software will enable computer clusters load on the system to achieve the best balance
psocluster
- 这是一个关于粒子群聚类的源代码，很有参考价值-This a type of particle clusters of source code, of great reference value!
K-meanCluster
- How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the f
dbscan
- DBSCAN是一个基于密度的聚类算法。改算法将具有足够高度的区域划分为簇，并可以在带有“噪声”的空间数据库中发现任意形状的聚类。-DBSCAN is a density-based clustering algorithm. Algorithm change will have enough height to the regional cluster. and to be with the \"noise\" of the spatial database found clusters of
codeblue.1.4.tar
- Sector is a system infrastructure software that provides functionality for distributed data storage, access, and analysis/processing. It automatically manages large volumetric data across servers or clusters, even those over distributed wide area hig
FuzzyClusteringToolbox
- 使用matlab实现的各种聚类算法,其中包括具体例子进行详细说明。-The purpose of the development of this toolbox was to compile a continuously extensible, standard tool, which is useful for any MATLAB user for one s aim. In Chapter 1 of the downloadable related documentation on
fisher_classify
- function [clusters,c,F]=fisher_classify(A,B,data) fisher判别法程序 输入A、B为已知类别样本的样本-变量矩阵，data为待分类样本 输出C为判别系数向量 -function [clusters, c, F] = fisher_classify (A, B, data) fisher discriminant method procedures input A, B for a sample of known typ
hartigansSLC_OpenCV
- hartigans Sequential Leader Clustering Algorithm in terms of OpenCV (ver.1.1) Sequential Leader algorithm: Hartigan, J. A. (1975), Clustering Algorithms. John Wiley and Sons, Inc., New York, NY. 1. Select maximum cluster "radius" 2
fish-mobile-a--clusters
- 实现人工鱼移动,聚群,追尾,捕食,迭代20次的效果-20 iterations of artificial fish, artificial fish mobile, clusters, rear-end collision, predation
ch05_Arrays-and-Clusters
- ch05_Arrays and Clusters.rar
Analysis-of-data-clusters-obtained-byself-organiz
- In order to reveal new structures in stock market behavior of the companies drawing up Dow Jones index we apply self-organizing maps (SOM) and group method of data handling (GMDH) algorithms. Using SOM techniques we obtain SOM-maps that establish
Data-Processing-on-Large-Clusters
- Abstract: Map-Reduce is a programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. Through a simple interface with two functions, map and reduce, this