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基于matlab的K均值聚类程序
- 基于matlab的K均值聚类程序。其中用IRIS数据进行验证，得到了很好的结果。文件中包含了演示后的结果图,Matlab-based K-means clustering procedure. Which use IRIS data verification, have had good results. File contains the results of the demonstration plan
k-means-and-cure-in-Iris-Data-Set
- 聚类算法实验,采用两种不同类型的聚类算法:基于划分的聚类方法k-means和基于层次的聚类方法CURE，采用的数据集是：Iris Data Set，数据集中共包含150组数据信息。 材料中有详细的说明文档，具体介绍了算法实现的细节，很容易理解-Clustering algorithm experiment, using two different types of clustering algorithm: Partition-based clustering method k-means
k-means-iris
- 针对著名的UCI机器学习数据库中的iris data的kmeans聚类分析程序，具有代表性-For the well-known UCI machine learning repository of the iris data of kmeans cluster analysis procedure, a representative
include
- 本程序实现对四维Iris.Data的分类处理，应用K-Means算法将其分为两类-This procedure to realize the four d Iris. The classification of the Data processing, the application of K-Means algorithm which is divided into two categories
K-Means.java K-means分群法
- K-Means.java K-means分群法(组数数据皆不固定，以读入档案， iris.txt)-K-Means.java K-means grouping method (group, none fixed the number of data in order to read the file, iris.txt)
Ckmedoids
- K-mean算法，并通过了IRIS数据的测试。-K-mean algorithm, and through the IRIS data testing.
ex-12
- K-Means.java K-means分群法(組數資料皆不固定，開小視窗選檔案:A or B or iris，10 runs + output至Excel)-K-Means.java K-means grouping method (the number of data groups, none is fixed, to open a small window, select the file: A or B or iris, 10 runs+ output to Excel)
K-MEANS
- 数据挖掘，K-means源码，数据集为iris-Data mining, K-means source code for the iris data set
famousz-misc
- k-means及Isodata 聚类算法的实现，用c++代码实现，输入数据为Iris，输出分类类结果。 包含Iris数据及所有头文件和.cpp文件。-Isodata k-means clustering algorithm and implementation, using c++ code implement,. the input data is the Iris, the output classification class results. contains Iris d
Cmeansclusteringmethods
- 本算法在vc++6.0中进行实验。分别就分解聚类和C-均值聚类两种方法在IRIS数据集上进行操作。分类前先将数据集中的样本顺序打乱形成混合数据。分解聚类中，采用前100个样本用对分法编制程序将数据分为两类。C-均值聚类采用全部的150个样本，将类别参数K设为3，将数据分为三类。-The algorithm in vc++6.0 in the experiment. Separate cluster and decomposition of two C-means clustering metho
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-MEANS
- 该文档主要讲述的是K-means算法分析Iris数据集-The document covers the K-means algorithm for Iris data set
Kmeans
- 用matlab编写的K均值算法，测试数据为Iris数据，经调试运行良好！实验结果稳定！-K-means algorithm using matlab, test data for the Iris data, through debugging and running! Stability of the experimental results.
k-means-for-iris
- 利用K均值聚类对鸢尾花样本进行聚类的matlab程序，包含源代码、样本数据、聚类结果-The use of K-means clustering method to classify iris sample matlab program, the program includes source code, sample data, the classification results
k-means-bayes-algorithm
- k-means和贝叶斯算法对iris数据进行测试-k-means algorithm and Bayesian test for iris data
K-Means-master
- 模糊C均值聚类算法的PYTHON实现，在UCI的IRIS数据集上实现-Fuzzy C-means clustering algorithm PYTHON realization, implemented on UCI s IRIS data set
k-means算法的Matlab实现以及Iris数据集
- k-means算法实现以及Iris数据集(Implementation of K-means algorithm and Iris data set)
k-means-for-iris
- 利用K均值聚类对鸢尾花样本进行聚类的matlab程序，包含源代码、样本数据、聚类结果(The matlab program of clustering iris samples by K-means clustering, including source code, sample data and clustering results)
can_use_kmeans
- K-means对iris数据集进行分类，可画出3维分类图(K-means to classify iris data set)
k_means
- 利用K均值算法对Iris数据集进行聚类，实现Iris数据集的无监督学习。(K-means algorithm is used to cluster iris data set to realize unsupervised learning.)