搜索资源列表
CART
- 数据挖掘算法，K-means聚类算法源代码，用于聚类分析-data mining algorithms, K-means clustering algorithm source code for the cluster analysis
fuzzy_k_means
- 数据挖掘算法，fuzzy-K-means聚类算法源代码，用于模糊聚类分析-data mining algorithms, fuzzy-K-means clustering algorithm source code for Fuzzy Cluster Analysis
KMEANS(matlab)
- Matlab环境下的k-means聚类算法，实现图像分割，很快阿！-K-means Clustering arithmetic based on Matlab platform.It s fast for Image-Division!
K-means-Clustering
- 根据模拟数据进行K均值聚类实验，有原始数据，聚类代码和相关图片，程序可用！-Analog data according to K-means clustering experiment, the original data, clustering code and picture, the program is available!
K-Means-master
- k均值聚类算法，自动产生一组数，并进行聚类，稍作修改可用于机器学习等方面使用-k-means clustering algorithm to automatically generate a set of numbers, and clustering, minor modifications can be used in other aspects of the use of machine learning
K-means
- 通过非监督分类中的K-均值聚类对Indian pines高光谱图像进行分类-Classification of hyperspectral images of pines Indian by K-means of non supervised classification
K-means
- K均值聚类方法，用于图像处理，图像分割，提取不同特征。-K-means clustering method
K
- K-MEANS聚类分析，用于实现目标识别效果~识别率较高~-K-MEAN Clustering analysis, used to achieve the target recognition effect ~ recognition rate is higher
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
k-means-clustering
- 关于k-均值聚类分析的R语言的代码及其应用-k-means clustering
K均值对iris数据集聚类
- k-means算法对irisdata数据集进行聚类(The k-means algorithm clustering the irisdata datasets)
85375535Kmeans
- K均值聚类算法是先随机选取K个对象作为初始的聚类中心。然后计算每个对象与各个种子聚类中心之间的距离，把每个对象分配给距离它最近的聚类中心(K means clustering algorithm is first randomly selected K objects as the initial clustering center. Then calculate the distance between each object and each seed cluster center and
kmeans&&ISODATA
- k-menas与ISODATA 非监督分类代码，希望对初学者有帮助。(K-menas and ISODATA unsupervised classification code, I hope to help beginners.)
fenlei
- K均值聚类分析，可实现2/3/4类的分类，适用于初学者，为实现5/6类的分类提供想法(k-means clustering analysis)
k-means算法2
- 使用该算法可以实现数据的聚类分析，非常适合初学者。(The algorithm can be used to achieve clustering analysis of data, ideal for beginners.)
kmean
- 一个学习k均值聚类的实例，代码实现了其基本原理，简单易懂，带有测试，训练数据集，可直接上手操作(A learning k-means clustering example, the code to achieve its basic principles, easy to understand, with a test, training data set can be used directly)
K_means
- 本代码可以根据类的初始中心位置和初始点总数，返回每个类的中心位置以及属于哪一类。(This code can return to the central position of each class and what class it belongs to, based on the initial center location and the total number of initial points of the class.)
ABC-K-means
- 基于改进人工蜂群算法的K均值聚类算法-喻金平-郑杰-梅宏标，matlab(K-means clustering algorithm based on improved artificial bee colony algorithm-Yu Jinping-Zheng Jie-Mei Hongbiao, matlab)
改进的基于划分算法的三维点云聚类matlab实现
- 根据网上基于划分法k-means的聚类算法，我做了改进。可以预设一个最大的类数和一个半径，自动划分合适的类。最终将随机三维点云聚类完成后显示为不同颜色。(According to the clustering algorithm based on partition K-means on the Internet, I improved it. A maximum number of classes and a radius can be preset to automatically divi
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))