搜索资源列表
KMEANS
- 数据挖掘中动态聚类的K-means算法,适合研究聚类人员。-Data Mining in the dynamic clustering of K-means algorithm for clustering research staff.
clustering
- 该程序包实现了三个模式识别的聚类算法,分别是K-means、LVQ2和GLVQ聚类算法。采用C++语言编写,开发环境是VS。 另外,压缩包中还提供了两个测试样本文件。-The package has three pattern recognition clustering algorithm, namely K-means, LVQ2 and GLVQ clustering algorithm. Using C++ language, development environment is VS.
kmean
- k-means 算法的工作过程说明如下:首先从n个数据对象任意选择 k 个对象作为初始聚类中心;而对于所剩下其它对象,则根据它们与这些聚类中心的相似度(距离),分别将它们分配给与其最相似的(聚类中心所代表的)聚类;然后再计算每个所获新聚类的聚类中心(该聚类中所有对象的均值);不断重复这一过程直到标准测度函数开始收敛为止。-k-means algorithm process as follows: First of all, the object data from the n choose k
KMEANS
- K-Means动态聚类算法源程序 在数据挖掘中的应用-K-Means dynamic algorithm source data mining application
clkmeans
- 将最大最小距离和k-means算法融合实现聚类-max-min distance and k-means
ClusteringToolbox
- 用于进行聚类分析的matlab工具箱,包括K-means、模糊聚类等。-Used for cluster analysis of the matlab toolbox.
xuzhuol
- 基于改进K-means的压缩IP 由于k-means本身受异常点影响较大,这里采用迭代k-means的方法,降低异常点的影响,减少计算量和提高聚类数目的灵活性。并添加合并异常聚类方法,提高聚类的均匀性-K-means based on improved compression IP As k-means itself is influenced by outliers, where an iterative k-means method to reduce the impact of o
kasp.tar
- 快速谱聚类算法的实现,使用R语言,在linux下运行-fast approximate spectral clustering implemented with K-means complete with R
dataset
- matlab 代码 k-means 算法 实现2-D数据的聚类-matlab code for k-means algorithm is 2-D data clustering
famousz-misc
- k-means及Isodata 聚类算法的实现,用c++代码实现,输入数据为Iris,输出分类类结果。 包含Iris数据及所有头文件和.cpp文件。-Isodata k-means clustering algorithm and implementation, using c++ code implement,. the input data is the Iris, the output classification class results. contains Iris d
KMEANS
- 基于K-Means动态聚类算法,应用于数据挖掘-Based on Dynamic K-Means clustering algorithm, used in data mining
k_meansc_meansCluster
- 基于k均值、c均值等聚类算法,应用于数据挖掘-Based on the mean k, c means clustering algorithm, etc., used in data mining
K_Means
- K均值算法,实现一种动态聚类法--迭代自组织数据分析算法,这是一种较为简单的K均值算法-K means algorithm, to achieve a dynamic clustering method- iterative self organizing data analysis algorithm, which is a relatively simple K-means algorithm
Clustering
- 对数值型数据进行聚类:实现了K-means和FCM算法-K-means,fuzzy c means
clusterds_demo
- clusterds_demo k-means 和DBSCAN聚类算法的演示程序,图形化输入数据,对话框输入参数,可以充分理解算法-clusterds_demo k-means' and DBSCAN clustering algorithm demo program, graphical input data, input parameters dialog box, you can fully understand the algorithm
meanshift
- 国外牛人写的聚类算法,是k-means算法的升级版-Written by foreign cattle clustering algorithm, k-means algorithm is an upgraded version of
KMEANS
- k-means C++ 源代码, 修正原来的错误, 增加的新功能 1、用vector实现其存储 2、直接在程序中读取数据集 3、结果可以保存到文件中 4、用户可以输入聚类个数 5、初始聚类中心随机选择(代码自动随机)-k-means C++ source code, fixes the original error, the increase in new features 1, 2, with the vector to achieve its store dire
kmeans
- 用于数据挖掘聚类分析的简单的K平均算法Matlab源代码-Simple K-means for data mining (Matlab)
kmenasofclusting
- k-means算法,经典的聚类算法,可以用于聚类,是用C++编写的-k-means algorithm, the classical clustering algorithm, can be used for clustering, is written in C++
kmeans
- 数据挖掘聚类算法中,K-means的matlab实现-Data mining clustering algorithm, K-means the matlab implementation