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k-means
- 数据挖掘，或者适用opencv上的图像处理功能-Image processing functions of data mining, or apply on opencv
K-means
- 此算法为k邻近算法，能很好的对数据进行分类，而且运算速度快-This algorithm k neighbor algorithm, can be very good for data classification and fast operation speed
k-mean
- 简单的K均值算法，使用matlab平台编程，两个文件一个是数据文件，一个是算法文件-Simple K-means algorithm, using matlab platform programming, one file is a data file, and the other is a algorithm file.
K-means
- KMeans算法，经典的数据挖掘算法，设置了三个中心点，初始化是采用读取数据集的三个点作为中心的。-KMeans Algorithm, it is very famous data mining algorithm, i set three center, and it was initialed by the data we classify.
k-means
- 采用聚类方法进行分群的方法，包含两个matlab文件，一个是需在程序中给定数据，一个使用excel给出数据。针对风电场分群构建，也可以用于其他的聚类分群场合-Clustering method using clustering method matlab contains two files, one is required in the program given the data, a given data using excel. For wind farm constructed gro
k-meansClustering
- 这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。-Where k-means clustering, is given in advance the number of classes contained in the original data, then the data contained similar characteristics grouped into a single class.
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.
xin-k-means
- 此程序中直接是关于具体数据的聚类划分，直接给出相应的数据。-This program is directly of clustering on specific data directly gives the corresponding data
RBF-k
- RBF-k均值聚类算法的matlab程序和样本数据，可用于RBF-k均值聚类算法的仿真。-RBF-k-means clustering algorithm matlab program and sample data, can be used to simulate the RBF-k-means clustering algorithm.
k
- 用K均值聚类分析把多组数据分成两类 本程序为给定20组数据（用矩阵A表示）分成B、C两组。-K-means clustering analysis of the multiple sets of data into two categories This program is given 20 sets of data (represented by the matrix A) into B, C groups.
K-Means
- matlab kmeans 程序说明与数据源代码-matlab kmeans source
k-means
- matlabk-means聚类多维数据分析-matlabk-means clustering multidimensional data analysis
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
- 机器学习中的kmeans算法用西瓜数据集4.0作为数据进行测试-Machine learning algorithms with watermelon kmeans data set 4.0 as the data for testing
k-means
- java实现kmeans算法，方便数据挖掘相关人员更直观了解整个算法的思想及实现过程-java achieve kmeans algorithm to facilitate data relevant personnel more intuitive understanding of the whole idea of mining algorithms and implementation process
K-means_C
- 用K-means算法实现数据聚类。首先利用C随机产生800个数据，并将这800个数据作为一组训练样本；其次利用K-means的原理跟方法将这组样本聚类成8个类，从而实现数据的分类。-Data Clustering with K-means Algorithm. First, 800 data were randomly generated by C and the 800 data were used as a set of training samples. Secondly, the K-m
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
kmeans2
- 此程序可以实现大型数据聚类算法，其中含有测试数据。(This program can achieve large data clustering algorithm, which contains test data)
kmeans
- 基于k均值的无监督聚类算法，输出有各个样本的类别标签，目标函数在每次迭代后的值，聚类中心以及聚类区间。内有测试数据，点击 test.m 可以完美运行。(The unsupervised clustering algorithm based on K means outputs the class labels of each sample, the value of the target function after each iteration, the clustering center a
kmean
- 负荷聚类，通过对负荷数据进行处理，提取典型用电方式，然后对典型用电方式进行聚类(load pattern clustering)