搜索资源列表
kmeans
- K均值有效执行++多元数据的聚类算法。它已经表明,该算法具有的总群集内距离的期望值是日志(K)的竞争力的上限。此外,K -均值++通常远高于香草收敛K均值少。-An efficient implementation of the k-means++ algorithm for clustering multivariate data. It has been shown that this algorithm has an upper bound for the expected value o
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
- 均值计算方法源码实现:分群的方法,就改成是一个最佳化的問題,換句话說,我們要如何选取 c 个群聚以及相关的群中心,使得 E 的值为最小。 -Method of calculating the mean source implementation: clustering method, based on the best change is a problem, in other words, how do we choose c a center cluster and related g
cluster
- 本程序是一个利用k-means进行聚类的算法,本程序绝对可用,是我自己用过的一个小程序。-This program is a use of k-means clustering algorithm, the program is absolutely free, that I used a small program.
cluster
- 基因聚类 主要有数据的预处理和K-means算法的聚类-Gene cluster are pre-processing of data and K-means clustering algorithm
kMeansCluster-Code-For-matlab.m
- The code for k-means cluster in matlab. It works well in matlab.
Algorithm-Cluster-1.50.tar
- Clustering algorithm using k means algorithm
k-means
- opencv k-meas 聚类分割,将图片分为2部分,主要针对道路特征-opencv , cluster
cluster-1.50
- hgc的clustering算法源码,包括k-means等-hgc s clustering algorithm source, including k-means method.
kmeans
- K均值聚类算法,短小实用。可以试一试哈。-k-means cluster. Matlab Code.
K-Mean-Clustering-Code-in-Matlab
- k 均值聚类算法 ,能有效的将数据分成k类 但是具有k参数难以确定的缺点。 -k-means algorithm can cluster data into K class but, the parameter K can not be selected easily.
cluster
- CLUSTER ALGORITMA K-MEANS
K-Means_Text_Cluster
- K-Means文本聚类python实现,文本聚类算法,人名排除歧义-Text Cluster by the algorithm of K-means(include texts), discrimination of name ambiguity.
k-means-clustering
- 用C语言程序通过先随机选取K个对象作为初始的聚类中心。然后计算每个对象与各个种子聚类中心之间的距离,把每个对象分配给距离它最近的聚类中心。聚类中心以及分配给它们的对象就代表一个聚类。一旦全部对象都被分配了,每个聚类的聚类中心会根据聚类中现有的对象被重新计算。-C Programming Language by first randomly selected the K object as initial cluster centers. And then calculate the distan
AP-cluster
- AP聚类算法,08年提出的一种优秀聚类算法,文档描述其执行过程及k-means和它的比较-AP cluster
K_means
- k-means聚类算法的实现,比较简单,一共有五个java文件。-k-means cluster algorithm
cluster
- 实现聚类分析的几种典型算法,包括Greedy、K-Means、FCM、Xie-Beni等。可以对提供的几个数据库文件进行聚类操作,并显示和统计结果的各项数据。程序具有基于C#的图形界面,操作直观方便。-Cluster analysis of several typical algorithms, Greedy, K-Means, FCM, Xie-Beni, etc.. The cluster provides several database files, and display the da
Cluster
- 使用k-means、k-media、层次聚类方法,并通过iris数据集测试-Using k-means, k-media, hierarchical clustering method, and through the iris data set test
UCI
- 利用k-means对UCI数据集进行聚类分析,程序中列举了数据集wine和heart数据集-Using the k- means cluster analysis was carried out on the UCI dataset, listed in the program data collection of wine and heart of data sets
Simulated-Annealing
- 由于K-means 聚类方法对遥感图像进行分类时,对训练样本的选取依赖性很大,容易陷入局部最优的陷阱的情况,本文提出利用模拟退化算法对K-means 的聚类进行优化以获得 全局最优解的分类新方案。并以多波段影像为例进行验证分析,结果表明该方法可行,收敛 结果优于K-means 聚类算法,分类精度相对传统的K-means 算法更高。-Because K-means clustering classification depend on the training sample selecti