搜索资源列表
Ksam
- 新颖的K均值聚类算法，以SAM作为两个向量的距离度量，取代原始的向量间的距离-Multi-spectral K-mean clustering with SAM as spectral similarty
k_means
- k均值的 咱们做非监督分类都用过 不想理解他的原理吗 很重要-k mean we do not want unsupervised classification are used to understand his theory is very important to you
PCA
- 自己写的PCA降维算法，还有模糊k均值大家可以参考一下-Write their own PCA dimensionality reduction algorithm, and fuzzy k means we can refer to
kmeans_JIT
- 使用了JIT的高效的k均值算法，因为使用了JIT加速，所以在统计工具箱下，比一般的k均值要快许多-Efficient K-Means using JIT (Matlab code) This code uses the JIT acceleration in Matlab, so it is much faster than k-means in the Statistics Toolbox. It is very simple and easy to read.
v
- matlab图像分割算法.风水岭算法.k-均值聚类变换-image segmentation algorithm matlab
Pattern-Recognization
- 通过编程了解和实现k均值聚类。-Understanding and implementation by programming the k means clustering.
022
- 遥感影像K均值分类，对遥感影像利用k均值算法进行分类，可自定义所分类别数和迭代阈值-K—Means Classification
KMEANS
- C++实现的简单的k均值聚类算法。最基本的聚类算法。-Kmeans clustering algorithm using VC++. It is one of the most fundamental algorithms.
kmeans
- 用k均值聚类实现随机n个数分类到k类中。 k和n是可变的。用图形化显示聚类结果。 需要把两个文件放在同一目录下，运行wkmeans2D即可。-k-means
NewK-means-clustering-algorithm
- 珍藏版，可实现，新K均值聚类算法，分为如下几个步骤： 一、初始化聚类中心 1、根据具体问题，凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。 2、用前C个样本作为初始聚类中心。 3、将全部样本随机地分成C类，计算每类的样本均值，将样本均值作为初始聚类中心。 二、初始聚类 1、按就近原则将样本归入各聚类中心所代表的类中。 2、取一样本，将其归入与其最近的聚类中心的那一类中，重新计算样本均值，更新聚类中心。然后取下一样本，
clustering-algorithm
- 聚类算法有很多种，该程序是基于K-均值聚类算法，主要用于图像的分割-There are many clustering algorithms, the program is based on the K-means clustering algorithm, mainly used for image segmentation
MapClassify
- 两种影像分类方法：K均值法和ISODATA法，程序里带了示例数据-Two image classification methods: K means method and the ISODATA method, procedures inner tube of the sample data
KMeansCluster
- k均值聚类的VC++实现，适合语音等方面聚类之用-k means clustering of VC++ implementation of voice, etc. for use in cluster
Kmeans-MATLAB
- 该代码能够实现K均值聚类算法对彩色图像分割，在MATLAB下实现。-The code can achieve K means clustering algorithm to color image segmentation, in MATLAB to achieve.
kjunzhi
- 本程序可以实现图像k均值聚类在数据挖掘中的相关算法。计算出图像的直方图-This program can image k means clustering in data mining correlation algorithm. Calculate the histogram
seghough
- K均值聚类法基于lab颜色空间分割图像，并用霍夫变换检测圆-K means clustering method is based on lab color space segmentation image and Hough transform to detect circles with
kMeansCluster
- K均值聚类算法，可用于预先定义好种类数的样本聚类-K means clustering algorithm
CPPK-means
- K均值聚类首先需要确定聚成几类，然后按照迭代的方法，计算类的重心，然后按照向量和类重心的聚类重新分类，反复重复，直到分类稳定或者重心稳定。-K means clustering first need to identify clustered into several categories, and then follow the iterative method to calculate the focus of the class, and then follow the center of
IsoDataaK-means
- 是用VS6.0编写的程序。实现了模式识别中的ISODATA算法和K均值算法。内附有测试数据。-made by VS6.0 C++ Isodata K-means
KMeans
- K均值(K-Means)聚类算法，采用模板方式实现，支持不同类型样本数据。-K-Means cluster algorithm, using template to suport any data type.