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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
cbrp.tar
- cbrp协议ns2实现，ns2平台下实现，基于簇的路由协议算法 经典！-ns2 realize cbrp agreement, ns2 platform realize, based on the cluster routing protocol algorithm classic!
cluster-1.37.tar
- 聚类算法包,包括K-Means,性能好，有例程-Clustering algorithm package, including K-Means, a good performance, there are routines
kmeans
- kmeans算法实现 a simple k-means clustering routine. returns the cluster labels of the data points in an array.-algorithm kmeans realize a simple k-means clustering routine.returns the cluster labels of the data points in
FuzzyClusterV3[VB]
- 聚类分析算法（FuzzyCluste），vb实现-Cluster analysis algorithm (FuzzyCluste), vb realize
FCM
- 模糊聚类分析传递闭包算法FCM的matlab程序，能对数据进行分类处理-Fuzzy Cluster Analysis of transitive closure of the FCM algorithm matlab program can deal with data classification
fcm_c
- 模糊聚类分析传递闭包法FCM的C语言程序， 能对数据进行分类，广泛应用于模式识别中-Fuzzy cluster analysis method FCM transitive closure of the C language program that can classify the data is widely used in Pattern Recognition
isodata_iris
- 聚类分析isodata算法的C程序，实现对iris数据集分类的功能-ISODATA cluster analysis algorithm C procedures, to achieve the classification of iris data set features
mode
- 用vc++开发的图像分类，包括聚类分析，模糊聚类，遗传算法聚类等。有界面，代码！-With vc++ Developed image classification, including cluster analysis, fuzzy clustering, genetic algorithms, such as clustering. Has interface code!
kmeansNetlab
- KMEANS Trains a k means cluster model.CENTRES = KMEANS(CENTRES, DATA, OPTIONS) uses the batch K-means algorithm to set the centres of a cluster model. The matrix DATA represents the data which is being clustered, wit
cluster-1.23.tar
- 聚类算法的C语言库，可以再多个平台下使用，与大家分享-Clustering algorithm of C language libraries, multiple platforms can be used to share with you
GuideandMeasurementReportofUsingpMatlab
- pMatlab is a toolsbox from MIT for running matlab in parallel style on a multi-core PC or a cluster environment. These two documents summary the usage of pMatlab and running time measurements on three simple Monte Carlo
fuzzy-c-cluster
- 这是关于模糊K聚类的pdf文件，供大家学习-This is on the K fuzzy clustering pdf document for everyone to learn
KClustering
- 能计算用户输入的聚类，并进行K分。 输出的结果为每次计算的中心点的坐标和每个点到中心的距离-Can be entered by the user computing cluster, and K points. Output of the calculation for each of the coordinates of the center and each point the distance to the center
oLitU9hX
- 这是一个聚类算法，其中含有对初始化聚类中心的优化。-This is a clustering algorithm, which contains the optimal cluster center initialization.
mopsoGECCO.tar
- The last step in training phase is refinement of the clusters found above. Although DynamicClustering counters all the basic k-means disadvantages, setting the intra-cluster similarity r may require experimentation
k-means
- 空间数据分析中最常用的是聚类分析,而K-MEANS算法是聚类分析中常用的,其主要思想是在给定的聚类数目下对多维(我做的是三维空间点)向量进行聚类,-Spatial data analysis is the most commonly used cluster analysis, while the K-MEANS algorithm is commonly used in cluster analysis, the main idea
bibao
- 闭包传递法的一个函数以及一个求最大生成树的函数,用于模糊聚类分析(matlab)-Closure of the transfer method for a function and a function of the maximum spanning tree for the fuzzy cluster analysis (matlab)
KMEANS
- K-MEANS算法 输入：聚类个数k，以及包含 n个数据对象的数据库。 输出：满足方差最小标准的k个聚类。 处理流程： （1） 从 n个数据对象任意选择 k 个对象作为初始聚类中心； （2） 循环（3）到（4）直到每个聚类不再发生变化为止 （3） 根据每个聚类对象的均值（中心对象），计算每个对象与这些中心对象的距离；并根据最小距离重新对相应对象进行划分；
kmeans1
- k-均值聚类算法实现灰度图像分割，输入图像矩阵和聚类中心个数，返回为最终的聚类中心和图像中每个像素所属类的编号（对应于图像矩阵）-k-means clustering algorithm to achieve gray-scale image segmentation, the input image matrix and the number of cluster centers, the return for the final i