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K-Mean聚类算法
- 本程序是基于vc++实现K-Mean聚类
K-均值聚类算法
- K-均值聚类算法，对数据进行聚类分析，可用于提取关键帧等。用matlab实现,K-means clustering algorithm, cluster analysis of data that can be used, such as key frame extraction. Using matlab to achieve
JAVA实现文本聚类，用到TF/IDF权重
- JAVA实现文本聚类，用到TF/IDF权重，用余弦夹角计算文本相似度，用k-means进行数据聚类等数学和统计 知识。,JAVA realization of text clustering, using TF/IDF weight, calculated using cosine angle between the text of similarity, using k-means clustering for data such as mathematical and statistical
k-rbf
- 程序是基于K均值聚类的RBF代码，很好的一个例子。-K means clustering procedure is based on the RBF code, a good example.
K-Means
- K均值聚类算法 C++实现的K均值聚类算法。-K means clustering algorithm C++ Achieved K-means clustering algorithm.
k-mean k均值聚类程序
- k均值聚类程序，虽然matlab中也有自带的，但是这个速度不错。-program for k means used for cluster
k-meams(sourcecode)
- C#实现k均值文本聚类算法，文本聚类C#源程序，k-means聚类算法-C# to achieve k means clustering algorithm, document clustering C# source code, k-means clustering algorithm
K-mean聚类的原理和MapReduce实现
- K-mean聚类的原理和MapReduce实现
kMeansCluster
- K-均值聚类，比较好的聚类方法，应用广泛-K-means clustering, a better clustering method, widely used
cluster
- k均值聚类算法源码（matlab） k均值聚类算法源码（matlab）-k-means clustering algorithm source code (matlab) k-means clustering algorithm source code (matlab)
k-centers
- 不同于k均值聚类的k中心聚类，2007年SCIENCE文章Clustering by Passing Messages Between Data Points 中的方法-Unlike k-means clustering of the k cluster centers, in 2007 SCIENCE article, Clustering by Passing Messages Between Data Points of the Method
K-means
- 均值为K的聚类算法，是一种对聚类数据进行的最简单的算法，广泛应用在各种场合中。-K mean clustering algorithm for clustering data is the most simple algorithm, widely used in various occasions.
kmean
- 包括K-均值聚类算法的思想介绍，kmeans的MATLAB代码，c语言代码、c++代码。-Including the K-means clustering algorithm introduced the idea, kmeans of MATLAB code, c language code, c++ code.-Entropy Based Subspace Clustering for Mining Data- ENCLUS- a new version of PROCLUS algorit
K均值聚类
- K均值聚类算法图像分割，最传统的一种分割方法(K mean clustering segmentation)
K-mean
- K-means算法是很典型的基于距离的聚类算法，采用距离作为相似性的评价指标，即认为两个对象的距离越近，其相似度就越大(K-means algorithm is a typical distance based clustering algorithm. The distance is used as the evaluation index of similarity, that is, the closer the distance between the two objects, the
K均值聚类在基于OpenCV的图像分割中的应用
- 介绍了传统的图像分割与K-均值聚类算法分割，然后利用OpenCV函数将其实现，并介绍了OpenCV中图像分割相关的基本函数。(This paper introduces the segmentation of traditional image segmentation and K- mean clustering algorithm, then uses OpenCV function to implement it, and introduces the basic functions of
k均值聚类
- 用VC++写的K均值聚类算法，可以直接使用(K mean clustering algorithm is written by VC++ , which can be used directly.)
基于聚类的细分研究
- 使用R语言进行聚类分析的例子，包括层次聚类，k均值聚类，密度聚类等(Examples of clustering analysis using R language, including hierarchical clustering, K mean clustering, density clustering, etc.)
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)
聚类算法
- 文件夹中主要有二维的K-means，gmm，mean-shift，三维的K-means聚类算法的程序，同时已经经过本人验证无误，可以成功运行，有问题的可以私下交流。(Folder mainly two-dimensional k-means, GMM, mean-shift, three-dimensional k-means clustering algorithm procedures, at the same time has been verified by myself, can be