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PhamDN05-kmeans
- k-means cluster algorithm
Km
- In data mining, 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. This results in a partitioning of the data space into Vo
k_means
- k-means聚类方法 编写k-means聚类方法对这些点进行聚类-k-means clustering method to write k-means clustering method to cluster these points
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
X-means-Extending-K-means
- X-means k-means扩展 论文 聚类-X-means Extending of k-means cluster
Ant-clustering-algorithm-with-K-harmonic-means-cl
- This paper tell about hybrid ant colony- kmeans algorithms. Clustered by ant colony is used for initial cluster for kmean algorithm.
5timbre-classification
- Timbre is described as the tone color of a sound which helps to distinguish between different sounds.For a single musical instrument sound the timbre can be classified into different categories using K-means cluster analysis.
Chinese-(1)
- K-MEANS algorithm Input: cluster number k, and contains n data object . Output: the minimum
dbscan-721ea2b3e634.tar
- K-MEANS algorithm Input: cluster number k, and contains n data object . Output: the minimum
K-Means
- 统计中的聚类分析，c语言程序以及说明。应用广泛-Statistical cluster analysis, c language program and instructions. Widely
recluster-in-wsn-by-using-data-aggregation-techni
- I am doing research in wireless sensor network in data aggregation. here cluster head send packet to base station .by using k means cluster algorthim A network is divided into k layer. k cluster are formed in k layer . each cluster has one cluster he
MonTestRandom
- k-means is one of the simplest unsupervised learning algorithms that solve the well known clustering problem. The procedure follows a simple and easy way to classify a given data set through a certain number of clusters (assume k clusters) fixed apri
k-junzhi
- 通过对K-均值算法的编程实现，加强对该算法的理解和认识。提高自身的知识水平和编程能力，认识模式识别在生活中的应用。 算法思想K-均值算法的主要思想是先在需要分类的数据中寻找K组数据作为初始聚类中心，然后计算其他数据距离这三个聚类中心的距离，将数据归入与其距离最近的聚类中心，之后再对这K个聚类的数据计算均值，作为新的聚类中心，继续以上步骤，直到新的聚类中心与上一次的聚类中心值相等时结束算法。-By programming K- means algorithm implementation, s
zkmeans
- Cluster Scheme using K-means
K-Means
- 对500个随机二维坐标点进行聚类，然后通过C++程序输出窗口输出。(Cluster Algorithm.Put the 500 2d points into 20 clusters.)