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Exam096 k均值算法
- 用c语言编写的k均值算法-prepared by the k-means Algorithm
k均值聚类算法
- k均值算法的源代码-k means algorithm source code
K-means_clustering_demo
- K-均值聚类算法 vc++图形演示程序-K-means clustering algorithm c++ demo program
KMeansClusterConsole
- K均值聚类算法，取前k个点为初始聚类中心，然后进行迭代聚类-K means clustering algorithm, fetch the first k points as initial cluster centers, then the iterative clustering
K-means
- 简单实用的k均值聚类算法，可以实现多位向量的简单聚类-Simple and practical k-means clustering algorithm, can achieve more than a simple vector clustering
k-means
- k均值聚类算法源码 聚类算法学习的实例功能-k-means cluster algorithm
sujuwajue
- 数据挖掘考试准备的算法源码，包含Aporio算法，K均值算法，层次分类算法，内含有使用说明，经过考试和实验通过。-Examination of data mining algorithms to prepare the source, including Aporio algorithm, K-means algorithm, hierarchical classification algorithm, after the adoption of examination and experime
k
- k平均聚类所谓k均值聚类方法是一种无监督的学习算法，它能用已知类数的数据聚类和预测。-k-average clustter
1
- k均值算法，用matlab实现的，数据挖掘-k-means
k-means
- k-均值聚类算法c语言版，经验证测试是可以运行
knear
- K均值算法，用于聚类，程序写得比较好，容量读-K means algorithm for clustering, procedures written better, capacity Reading
K-means-cSharp--code
- k均值算法是模式识别的聚分类问题，这是用C#实现其算法-K-means algorithm is pattern recognition of poly classification problem, this is written in c# realize its algorithm
K-means
- 用matlab实现k均值算法，不用库函数(Implementation of K mean algorithm)
ISODATA算法2
- 用ISODATA算法进行聚类，在K-均值算法的基础上加入了分裂与合并的步骤(ISODATA algorithm for classification)
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)
k均值聚类算法
- 根据k均值聚类的原理，实现一些数字的聚类，但是具体类别数需要自己设置(Clustering of some numbers by K mean clustering)
MATLAB实现MAP EM算法全集
- MATLAB实现EM算法和k均值算法，有资料和源代码(MATLAB to achieve EM algorithm and K means algorithm, data and source code)
KMEANS
- C++编程实现数据挖掘中的聚类分析 使用K均值算法(C++ programming to achieve data mining clustering analysis using k-means algorithm)
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))