搜索资源列表
K-junzhi
- 这是K均值聚类算法的程序,应用相当广泛的,比如在模式识别里就很重要.-This is the K-means clustering algorithm, application fairly extensive, such as pattern recognition is important to Lane.
K-Mean1
- 编写K-均值聚类算法程序,对下图所示数据进行聚类分析(选k=2)-prepare K-means clustering algorithm, the data shown in the chart below cluster analysis (EAC k = 2)
对k-means聚类算法的改进
- K均值算法的一个改进算法,简单实用,但是有点简单。-K-means algorithm of an improved algorithm is simple and practical, but a bit simple.
textureseg
- 用多尺度Gabor小波滤波器组实现纹理分割,其中聚类算法采用K均值聚类,本科毕业设计,省优秀-multi-scale Gabor wavelet,texture segmentation,k-mean clustering
k-means
- K-means均值聚类算法,用C语言实现 k-均值聚类算法 -Means K-means clustering algorithm, using C language realization of k-means clustering algorithm
Ksam
- 新颖的K均值聚类算法,以SAM作为两个向量的距离度量,取代原始的向量间的距离-Multi-spectral K-mean clustering with SAM as spectral similarty
mean-K-KPCA
- 通过核 K- 均值聚类的方法对语音帧进行聚类 , 由于聚类的中心能够很好地代表类内的特征, 用中心样本帧取代该类, 减少了核矩阵的维数, 然后再采用稀疏 KPCA方法对核矩阵进行特征提取。-Through the nuclear K-means clustering method for clustering of speech frames, the cluster center can be a good representative of the class characteristics
改进后的k均值聚类算法
- 这是加以改进后的聚类算法,适合研究聚类的学者使用。
Kjunzhi
- 一个简单的k均值聚类例程,适合数据挖掘初学者练习(A simple K mean clustering routines, practice for data mining beginners.)
K均值对图像进行聚类分析
- 用k-means算法对图像进行聚类,适合于初学者(K-means algorithm for clustering images, suitable for beginners)
99273863K-means-clustering-algorithm
- K-均值聚类算法。可自由输入初始聚类中心的个数和其坐标。(K- means clustering algorithm. The number of initial cluster centers and its coordinates can be freely entered.)
85375535Kmeans
- K均值聚类算法是先随机选取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(K means clustering algorithm is first randomly selected K objects as the initial clustering center. Then calculate the distance between each object and each seed cluster center and
《MATLAB统计分析与应用》程序与数据
- 数据的导入导出,将数据写入到txt,从TXT读取数据;数据预处理,归一化处理;聚类分析,K均值聚类等(Import and export data, write data to TXT, read data from TXT, data preprocessing, normalization processing, clustering analysis, K clustering, etc.)
kmeansuanfa
- 对大量的数据通过matlab软件,运用k均值聚类算法进行分类,(By using matlab software, a large number of data are classified by using k-means clustering algorithm.)
ksuanfa
- 对大量的数据通过matlab软件,运用k均值聚类算法进行分类,上传文件中含例子(A large number of data are classified by matlab software, using k-means clustering algorithm to classify and upload files with examples)
fenlei
- K均值聚类分析,可实现2/3/4类的分类,适用于初学者,为实现5/6类的分类提供想法(k-means clustering analysis)
K均值算法程序
- K均值聚类算法,实现将数据分类,分为两类聚类(K means clustering algorithm to achieve data classification, divided into two categories of clusters)
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)
Matlab聚类分析
- 分别运用分层聚类、K均值聚类以及高斯混合模型来进行分析
kmeans
- 利用k均值聚类算法对数据进行聚类分析(数据点通过随机生成)(Using k-means clustering algorithm to cluster data (data points are generated randomly))