搜索资源列表
kmeans(cp2Bp2B)
- kmeans聚类算法实现图像分割， 基于K-MEAN的图像分割,方便实用，对于图像处理的研究生很有参考价值的！-kmeans clustering algorithm for image segmentation, image segmentation based on K-MEAN, convenient and practical, for image processing graduate of great reference value!
PRJ_Final
- K-mean Algorithm Initialisation: set seed points Assign each object to the cluster with the nearest seed point Compute seed points as the centroids of the clusters of the current partition (the centroid is the centre, i.e., mean point, of th
kmeanhar
- a simple yet effective code for k mean clustering algorithm
IMAGEPROCESS
- 基于纹理度量的图像分割，适用于遥感图像，利用到K-mean算法。-Image segmentation based on texture measurement, suitable for remote sensing image, using K-mean algorithm
KMeans
- k-Mean 聚类,是聚类方法中运用最广泛的一种聚类算法-K-means clustering
graph_kmean_1cen
- Graph K-mean algorithm using 1 replaced centroid
code-kmean
- K-mean matlab code example
kmeanclustringapproach
- k-mean clustring method
k_mean
- k-mean data clustering
fuzme_matlab
- Fuzzy k mean code -Fuzzy k mean code
CircleDetect
- 霍夫变换，圆检测，硬币检测，图片中硬币价格识别，K-mean，高斯滤波,边缘检测，gradient，包括硬币实例图片。自己写的函数，不用toolbox。-hough transform, circle detect, coin detect, coin prize calculate, edge detect, gradient, K-mean, self-define function, no toolbox library.
kjunzhi
- 利用k均值算法将两个female和male包含身高与体重的100个样本进行类别数为2的聚类-Using the K mean algorithm, 100 female and male were clustered with two samples of height and weight for 2 of the clusters.
FNN
- 非常好用的模糊神经网络程序，中间的K-mean方法比较简单，自己添加以下即可！-The program very easy to use fuzzy neural network, k-mean middle part is relatively simple, what you can add your own!
V7
- Detection of viruses in tomatoes leaf based on K-Mean clustering algorithm-Detection of viruses in tomatoes leaf based on K-Mean clustering algorithm
k_means
- K-mean 算法是 J.B.MacQueen 在 1967 年提出的，是到目前为止应用最广泛最成熟的一种聚类分析方法。因该算法具有简单快速、适于处理大数据集等优点，目前，已被广泛应用于科学研究和工业应用中。-K-mean algorithm is JBMacQueen proposed in 1967, is by far the most mature and most widely used of a clustering analysis. Because the algorithm i
Kmeans1
- 利用K-mean的方法对样本进行聚类，只需要输入训练样本的地址和所要聚类的个数就可以完成聚类-The method of using K- mean to clustering samples, only need to input the training sample address and the number of clustering，and then it can be completed by clustering
RBF
- 使用k-mean确定RBF网络隐层中心点，后使用改进的梯度下降算法实现径向基神经网络的c++源程序，开发环境vs2010，可直接加载到自己的项目中。-Determined using k-mean RBF hidden layer center, the use of the improved gradient descent algorithm RBF neural network c++ source code, development environment vs2010
EM
- EM 算法，先K-mean 聚类，然后LGB分裂-EM algorithm, the first K-mean clustering, then LGB split
K-means-cluster
- k-means算法是一种动态聚类算法，基本原理如下[24]：首先预先定义分类数k，并随机或按一定的原则选取k个样品作为初始聚类中心；然后按照就近的原则将其余的样品进行归类，得出一个初始的分类方案，并计算各类别的均值来更新聚类中心；再根据新的聚类中心对样品进行重新分类，反复循环此过程，直到聚类中心收敛为止。-K- means algorithm is a dynamic clustering algorithm, the basic principle of [24] as follows: fi
test
- k-mean是的自动实现，具体采用欧式距离，效果还行，有兴趣的可以下载-K- mean yes automatically, the specific using Euclidean distance, the effect are ok, interested can download