搜索资源列表
K_average
- 模式识别的经典算法之一，动态聚类的k均值算法，采用matlab进行编程，并对分类进行了画图分析。-the classic pattern recognition algorithms, dynamic clustering algorithm k mean using Matlab programming, as well as classification of the class analysis.
2655143923
- 此程序是在VC环境下实现k-means均值聚类算法-this procedure is in VC environment to achieve k-means clustering algorithm Mean
texture3
- 本程序在对图像进行纹理分析（基于共发矩阵的方法）的基础上，获取图像不同区域的纹理特征，针对这些纹理特征，采用聚类（K-mean)的分类算法对图像进行区域划分！-procedures in the right image texture analysis (based on total fat matrix method), on the basis of access to different regions of the image texture features, these featur
textureA2
- 本程序在对图像进行纹理分析（由于共发矩阵的方法效果很不好，本程序采用基于频率域的纹理分析算法）的基础上，获取图像不同区域的纹理特征，针对这些纹理特征，采用聚类（K-mean)的分类算法对图像进行区域划分！-procedures in the right image texture analysis (due to a total of hair matrix, the effect is very bad, the program uses a frequency domain based on
UPublic
- 一个用delphi 写的图像,K均值(K-means)聚类算法-Written with the image of a delphi, K mean (K-means) clustering algorithm
k_means
- k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。-In statistics and machine learning, k-means clustering is a method of cluster analysis which aims to partition n observations into
PatternRecognition
- 对图像利用ＩＳＯＤＡＴＡ与Ｋ均值算法进行聚类分析-Clustering analysis for image by ISODATA and K-Mean Algorithm
k_means
- In statistics and machine learning, k-means clustering is a method of cluster analysis which aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean. It is similar to the expectation-max
procustesAlign
- Performs Procustes point alignment on a group of point sets. Method rigidly aligns, shifts, and scales points to reduce mean square error. Method is described in: B. Klare, P Mallapragada, A.K. Jain, and K. Davis, "Clustering Face Carvings: E
Image_Clust
- Title: Image Clutering K-means and Mean Shift) delphi implemetation Descr iption: This delphi program contains image clustering algorithms K-means and Mean shift. Contains 2 pas file for kmeans and mean shift. by chamika deshan
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，
Kmeans-julei
- 动态聚类的k均值算法,采用matlab编程,内有多个子程序，和一个主程序-dynamic clustering algorithm k mean using matlab
FunK_meanPolyD
- K-MEAN聚类算法功能展示，是一个多维的算法(K-MEAN clustering algorithm function display, is a multi-dimensional algorithm)
81801236k.matlab
- 利用matlab实现k均值聚类算法，亲自调试通过，对于学习k均值聚类算法有很大帮助(Using MATLAB to achieve K means clustering algorithm, personally debugging through, for learning K mean clustering algorithm is very helpful)
聚类分析
- 聚类分析算法 k均值算法 对地图上的点进行聚类事例(Clustering analysis algorithm k mean algorithm for clustering of points on maps)
IABC_KMC_test_on_Iris_wine_glass
- 克服K均值聚类算法易受初始聚类中心影响的缺点，优化K均值聚类算法(The K mean clustering algorithm is easily affected by the initial cluster center, and the K mean clustering algorithm is optimized.)
七个RBF神经网络的源程序
- 包含了RBF源代码，可以用于RBF神经网络编程，其中包括RBF聚类，K均值聚类等(It includes the RBF source code, which can be used for RBF neural network programming, including RBF clustering, K mean clustering, etc.)
基于聚类的细分研究
- 使用R语言进行聚类分析的例子，包括层次聚类，k均值聚类，密度聚类等(Examples of clustering analysis using R language, including hierarchical clustering, K mean clustering, density clustering, etc.)
kmean
- 确定K均值最佳聚类数，把数据导入后运行即可(Determining the best clustering number of K mean)
改进的基于划分算法的三维点云聚类matlab实现
- 根据网上基于划分法k-means的聚类算法，我做了改进。可以预设一个最大的类数和一个半径，自动划分合适的类。最终将随机三维点云聚类完成后显示为不同颜色。(According to the clustering algorithm based on partition K-means on the Internet, I improved it. A maximum number of classes and a radius can be preset to automatically divi