搜索资源列表
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)
kcluster
- 一种基于软划分方法的聚类方法——模糊k均值法聚类分析。-A division of methods based on soft clustering method- fuzzy k-means cluster analysis.
zfk_example
- 聚类分析里的k均值（kmeans）算法的matlab实现，是老师即将出的书里，我给写的例子，大家看看吧。 -Where k-means cluster analysis (kmeans) algorithm matlab implementation, a teacher is leaving the book, I give examples of writing, we take a look at bar.
kmeans
- 使用K－均值聚类算法在IRIS数据上进行聚类分析.-K-means clustering algorithm using IRIS data in the cluster analysis.
k
- 模式识别中的K均值聚类分析方法，该方法力偶那个迭代过程来进行处理，一步步逼近结果-Pattern Recognition Analysis of K-means clustering method Couple iterative process to deal with that, step by step approach results
k_mean
- 在聚类分析中，K-均值聚类算法（k-means algorithm）是无监督分类中的一种基本方法，其也称为C-均值算法，其基本思想是：通过迭代的方法，逐次更新各聚类中心的值，直至得到最好的聚类结果。 -In cluster analysis, K-means clustering algorithm (k-means algorithm) is unsupervised classification is a basic method, which is also known as C
Untitled3
- K均值聚类分析，好东西啊，想认真学习matlab的认真看下-K-means clustering analysis, a good thing, ah, want to seriously look carefully to learn matlab
Kjunzhi
- K均值聚类。加深对K均值聚类分析算法的理解，掌握K 均值聚类分析分类器的设计方法。-K-means clustering. Deepen the K-means clustering algorithm to understand and master K-means clustering analysis classifier design method
jlfx
- matlab聚类分析的几个例程 包括系统聚类的法案分析 K均值聚类的法的案例分析 模糊C均值聚类分析的典型案例-matlab clustering analysis of several routines, including hierarchical clustering analysis of K-means clustering Act case law analysis of typical cases Fuzzy C-Means Clustering Analysis
evaluation
- 基于MATLAB编写的集对分析与K均值聚类相结合的环境风险评价方法，熵权法作为指标权重确定方法。-MATLAB based on set prepared for analysis of environmental risk assessment and K-means clustering method of combining, entropy law as a method of determining the index weight.
Kmeans
- K均值聚类分析的matlab算法程序，用于对一系列的数据点进行聚类分析。-K-means clustering algorithm MATLAB program.
K-Means-Clustering-and-PCA
- 此代码为matlab代码，分为两个部分。第一部分实现K均值聚类算法应用它来压缩图像。在第二部分中，你将使用主成份分析法pca来实现人脸图像的低维表示。 -This code for the matlab code, is divided into two parts. The first part of the implementation of the K means clustering algorithm to compress the image. In the second par
moshishibie
- 基于matlab的模式识别基础实例源代码，包括贝叶斯分类器，Fisher线性判别，主成分分析，k均值聚类等。-Based on pattern recognition based matlab examples of source code, including Bayesian classifier, Fisher linear discriminant analysis, principal component analysis, k-means clustering.
Matlabalgorithmlibrary
- MATLAB算法库，包含K均值聚类-分类模型，logistics回归-用于决策，非线性拟合，回归分析模型，支持向量机SVM-用于分类决策，主成分分析PCA-用于决策，TXT格式，适用于数学建模-MATLAB algorithm library, including K-means clustering- classification model, logistics regression- for decision making, nonlinear fitting, regression an
ISODATA MATLAB编码
- 迭代自组织数据分析算法（Iterative Self-Organizing Data Analysis Techniques Algorithm，ISODATA）与K均值算法有相似之处，即聚类中心的位置同样是通过样本均值的迭代运算决定。不同的是，这种算法在运算的过程中聚类中心数目不是固定不变的，而是反复进行修改，以得到较合理的类别数K，这种修改通过模式类的合并和分裂来实现，合并和分裂在一组预先选定的参数指导下进行。
聚类分析程序
- 聚类分析程序 包括系统聚类 样品系统聚类 变量系统聚类 K均值聚类 模糊C均值聚类(Cluster analysis program)
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)
聚类分析程序
- 包含了各类聚类分析程序。主要包括系统聚类，基于欧氏距离的聚类，变量系统聚类和K均值聚类(It includes all kinds of cluster analysis programs. It mainly includes system clustering, Euclidean distance based clustering, variable system clustering and K-means clustering)
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
k均值聚类
- 通过比较自编MATLAB 的k-means 算法程序和SPSS 中自带的k-means聚类工具，对两个数据集聚类，并分析了聚类结果。(By comparing the k-means algorithm program of self-compiled MATLAB with the K-means clustering tool of SPSS, two data sets are clustered and the clustering results are analyzed.)