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K-Means
- K-MENAS算法是最简单的聚类算法，适合对于初学者的学习和改进使用-K-MENAS algorithm is a clustering algorithm is the most simple, suitable for beginners to learn and use improved
k-means-original
- k-menas算法是最简单的聚类算法，算法内详细介绍了各个函数和功能，对初学者很有借鉴意义-K-MEANS algorithm is one of the most simple clustering algorithm, there are different form, this is one of them, a reference for beginners
k-means-Java
- 用JAVA实现k-means算法，其中聚类方法使用余弦相似度,带运行界面。完美运行。-Using JAVA k-means algorithm, clustering method using the cosine similarity
k-means
- K均值算法，将数据矩阵命名为data，设置聚类簇个数k，可对多维数据进行聚类。-K mean algorithm, the data matrix is named data, set the number of clusters K, can be used to cluster the multi-dimensional data.
Desktop
- K均值聚类算法，对风电机组功率数据进行聚类分析，包括详细的程序说明。 只要把这两个文件放入一个空文件夹下，在MATLAB中执行m文件，就可得到聚类结果。-K-means clustering algorithm, the wind turbine power data clustering analysis, including a detailed descr iption of the procedures. As long as these two files into an empt
MultKmeans
- 改进的K-means聚类算法。用于处理空间聚类问题。-The improved K means clustering algorithm.To deal with spatial clustering problem.
The-optimization-of-K-means
- 对k-means算法的优化，通过优化初始聚类中心的选择-The optimization of K-means algorithm by improving the selection of initial clustering centers
K-means
- K-means算法,一种聚类方法，其每个类别均用该类中所有数据的平均值（或加权平均值）来表-K-means Algorithm
k_means
- k-means聚类算法，该算法已经经过验证，描述了聚类的过程-k-means clustering algorithm, which has been validated, we describe the process of clustering
my-k-means
- 这是一个k-means聚类算法，将一个四维量（比如有明确物理意义的花瓣长宽花萼长宽)按照几个中心点分成几类-This is a k-means clustering algorithm, a four-dimensional volume (such as a clear physical meaning petals calyx length and width aspect) is divided into several categories according to several ce
k-means-by-LR
- 标准的数据挖掘聚类算法 k均值聚类 k-means聚类 严格按照标准算法执行 简单高效-Standard data mining clustering algorithm k-means clustering In strict accordance with the standard algorithm is simple and efficient execution
K-means-Ensemble
- 该算法是基聚类算法为K-means，然后再进行聚类集成，方法为投票法-The algorithm is based on clustering algorithm for K-means, and then the clustering ensemble, method for voting
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
- k-means聚类算法 用C++实现 聚类采用数据为二维数据 保存在当前目录下的data.txt文件中-K-means clustering algorithm C++ implementation
K-meansbased-on-image-segmentation
- 基于K-means聚类算法的图像分割 代码及实验测试结果-K-means clustering algorithm based on image segmentation code and some experimental results
Cluster
- 机器学习和数据挖掘中常用的K-means聚类算法，包含两个文件，kmeans.py是Python实现代码，bank-data.csv是测试数据-Machine learning and data mining commonly used K-means clustering algorithm contains two files, kmeans.py is a Python implementation code, bank-data.csv test data
k-means
- 简单实现聚类算法中的经典k-menans算法，实现数据是二维数据- U7B80 u5B5 u5B9 u7B0 u803A u7R09 u7B09 u7B09
K_Means
- K-Means是聚类算法中的一种，其中K表示类别数，Means表示均值。顾名思义K-Means是一种通过均值对数据点进行聚类的算法。K-Means算法通过预先设定的K值及每个类别的初始质心对相似的数据点进行划分。并通过划分后的均值迭代优化获得最优的聚类结果。(K-Means is one of the clustering algorithms, in which K represents the number of classes, and Means means the mean. As t
EWKM
- 子空间聚类算法EWKM (Entropy Weighting K-Means) 在matlab上的实现。(Entropy Weighting K-means which is one of the subspace clustering algorithm written in Matlab.)
K-means
- 一种聚类算法：K-means聚类，实测绝对没有问题(A clustering algorithm: K-means clustering, no problem is absolutely no problem)