搜索资源列表
K-均值聚类算法
- K-均值聚类算法的matlab源程序,K-均值聚类算法的matlab源程序
imgkmeans
- 将K均值算法用于图像分割,输入的是彩色图像,转换为灰度图像进行分割,输出结果为灰度图像.利用灰度做为特征对每个像素进行聚类,由于光照等原因,有时应该属于一个物体的像素,其灰度值也会有很大的差别,可能导致对该像素的聚类发生错误.在分割结果中,该物体表面会出现一些不同于其它像素的噪声点,因此,算法的最后,对结果进行一次中值滤波,以消除噪声,达到平滑图像的作用-The K means algorithm for image segmentation, the input is a color imag
Kmeans_grayimage
- 简单的灰度图像的K均值聚类分割,Matlab实现-gray image segmentation using K-means clustering by matlab.
matlab-code
- 模式识别c均值聚类,也陈k均值,是模式识别中最最要的聚类方法之一。-Pattern Recognition, c-means clustering, and Chen k means, is far the most to the clustering pattern recognition methods.
clustering
- 模糊聚类算法,K-means and K-medoid algorithms,Fuzzy C-means algorithm,The Gustafson{Kessel algorithm,The Gath{Geva algorithm-Fuzzy clustering algorithm, K-means and K-medoid algorithms, Fuzzy C-means algorithm, The Gustafson (Kessel algorithm, The Gath (Gev
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.
k-means-algorithm-program
- 用于实现k-means聚类分析的matlab代码-Used to implement k-means clustering analysis matlab code
ISODATA MATLAB编码
- 迭代自组织数据分析算法(Iterative Self-Organizing Data Analysis Techniques Algorithm,ISODATA)与K均值算法有相似之处,即聚类中心的位置同样是通过样本均值的迭代运算决定。不同的是,这种算法在运算的过程中聚类中心数目不是固定不变的,而是反复进行修改,以得到较合理的类别数K,这种修改通过模式类的合并和分裂来实现,合并和分裂在一组预先选定的参数指导下进行。
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-Means PCA降维
- K-Means算法,不要求建立模型之后对结果进行新的预测,没有相应的标签,只是根据数据的特征对数据进行聚类。主成分分析降维对数据进行可视化操作,对features进行降维.(K-Means algorithm does not require the establishment of the model after the new prediction of the results, there is no corresponding tag, but only on the character
k-means
- 此代码可以对图像很好的聚类,文件里面有原始图像,也有聚类后的图像,聚类的效果挺好的,大家可以看看(This code can make a good clustering of images. In the file, there are original images, and there are also images of clustering. The effect of clustering is good. You can have a look at it)
《MATLAB统计分析与应用》程序与数据
- 数据的导入导出,将数据写入到txt,从TXT读取数据;数据预处理,归一化处理;聚类分析,K均值聚类等(Import and export data, write data to TXT, read data from TXT, data preprocessing, normalization processing, clustering analysis, K clustering, etc.)
1、K-means学习
- K-means算法MATLAB仿真,利用一副图像作为数据实现K聚类算法仿真(K-means algorithm, MATLAB simulation)
AP聚类
- AP聚类算法是基于数据点间的"信息传递"的一种聚类算法。与k-均值算法或k中心点算法不同,AP算法不需要在运行算法之前确定聚类的个数。(AP clustering algorithm is a kind of clustering algorithm based on "information transfer" between data points. Unlike the k- mean algorithm or the k center point
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)
DensityClust [Matlab 1.2]
- 采用密度的聚类算法,,聚类程序有两个,采用不同的K值进行计算(Using the density clustering algorithm, there are two clustering programs, which are calculated with different K values.)
K-means
- K-means算法是硬聚类算法,是典型的基于原型的目标函数聚类方法的代表,它是数据点到原型的某种距离作为优化的目标函数,利用函数求极值的方法得到迭代运算的调整规则。K-means算法以欧式距离作为相似度测度,它是求对应某一初始聚类中心向量V最优分类,使得评价指标J最小。算法采用误差平方和准则函数作为聚类准则函数。(The K-means algorithm is a hard clustering algorithm, which is representative of the prototy
K-means
- 利用MATLAB实现K均值聚类算法,加深对该算法的理解。(We use MATLAB to achieve K mean clustering algorithm to deepen our understanding of the algorithm.)
基于 K-means 聚类算法的图像区域分割
- 基于K-means聚类算法的图像区域分割(Image region segmentation based on K-means clustering algorithm)
k-means-for-iris
- 利用K均值聚类对鸢尾花样本进行聚类的matlab程序,包含源代码、样本数据、聚类结果(The matlab program of clustering iris samples by K-means clustering, including source code, sample data and clustering results)