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将维对分和K均值算法分割图像
- 利用聚类算法分割图像，将维对分法只可将图像分为2部分，可以作为二值化的代码,K-均值法可将图像分为任意多部分。程序直接采用R、G、B三色作为特征参数，聚类中心为随机值，当然也可以采用其他参数，程序编译为EXE文件后速度还可以接受，但尚有改进的余地，那位高手有空修改的话，请给我也发份代码。-clustering algorithm using image segmentation, Victoria right method can only image is divided into two p
KMeansV
- k-means聚类算法在二维平面上的可视化实现 聚类时可以设置类数和迭代阈值 聚类结果用色彩和类圆清楚的表现出来-k-means clustering algorithm in a two-dimensional plane with the Visualization of clustering can be set up several categories and iterative threshold Clustering results using color and clas
KMEANS
- 对二维数组的最基础的K-means聚类算法的c++实现-Two-dimensional array of the most basic K-means clustering algorithm c++ to achieve
ordinary_algorithm_for_pattern_recognition
- 使用C语言实现的一些简单模式识别聚类算法，用于简单的二维坐标系点的聚类。有最短距离算法、K均值算法、近邻算法、fcm算法、最大最小距离算法。-Using the C language implementation of some simple pattern recognition clustering algorithm for a simple two-dimensional coordinate system point of clustering. Has the shortest di
kmeans
- java k均值源码，实现了k-means的算法，并给出界面显示。实例中通过二维空间中的点进行聚类。-java k-means algorithm, display the cluster result on the two demension.
kmeans
- 基于matlab的K-means聚类算法的实现以及二维随机点的聚类结果-Matlab-based K-means clustering algorithm
K-average(N-dimension)
- K均值聚类算法实现有二维的聚类扩展到任意维样本点的聚类，代码中附加了详细的原理性说明，还有相关例子提示，效果不错-K-means clustering algorithm to achieve a two-dimensional clustering extends to any dimension of the cluster sample points, the code attached to the principle of detailed instructions, and tips
K-MEANS-N
- K均值聚类算法实现有二维的聚类扩展到任意维样本点的聚类.-K-means clustering algorithm to achieve a two-dimensional clustering extends to any dimension of the cluster sample points.
k-means
- c++实现k均值源码，实现了k-means的算法，并给出界面显示。实例中通过二维空间中的点进行聚类-c++ k-means algorithm, display the cluster result on the two demension
[emuch.net]K-means
- 简易k-means聚类算法实例，针对二维数据，自带简易数据矩阵，分析结果有输出图像。-Simple k-means clustering algorithm example, for two-dimensional data, comes with simple data matrix, analysis results output image.
k-meansaSOFM
- 已知一组二维模式矢量如下（20个）,利用k均值聚类算法将模式集分类，并计算出聚类中心。利用输入层为2个神经元，输出层结构为7*7方阵的自组织映射（SOFM）对同样模式进行聚类-Given a set of two-dimensional pattern vector as follows (20), the use of k-means clustering algorithm to classify the pattern set, and calculate the cluster cent
k-means
- 这是k-means聚类算法的matlab仿真实现,程序中分别有二维控件和三维空间基于k-means的聚类demo-This is k- means clustering algorithm of matlab simulation implementation, respectively in the program have two-dimensional controls and three-dimensional space based on k- means cluster demo
K-MEANS
- k-means聚类算法 用C++实现 聚类采用数据为二维数据 保存在当前目录下的data.txt文件中-K-means clustering algorithm C++ implementation
paosan
- 可实现对二维数据的聚类，应用小区域方差对比，程序简单，基于K均值的PSO聚类算法。- Can realize the two-dimensional data clustering, Application of small area variance comparison, simple procedures, K-means clustering algorithm based on the PSO.
K_means
- MATLAB实现的k-means聚类算法，自带测试以及数据集，数据集分为二维和三维数据。-k-means clustering algorithm implemented in MATLAB, and has a test data set, the data set is divided into two and three dimensional data.
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
K-Means
- 对500个随机二维坐标点进行聚类，然后通过C++程序输出窗口输出。(Cluster Algorithm.Put the 500 2d points into 20 clusters.)
k-means-matlab
- 利用k-means算法实现二维平面点的聚类，包括了运行源代码和结果图(The k-means algorithm is used to realize the clustering of two-dimensional plane points, including the running source code and the result graph)
K---MEANS
- 随机生成1000个二维坐标点并用K-means算法计算聚类结果(1000 two-dimensional coordinate points are generated randomly and the clustering results are calculated by K-means algorithm)
聚类算法
- 文件夹中主要有二维的K-means，gmm，mean-shift，三维的K-means聚类算法的程序，同时已经经过本人验证无误，可以成功运行，有问题的可以私下交流。(Folder mainly two-dimensional k-means, GMM, mean-shift, three-dimensional k-means clustering algorithm procedures, at the same time has been verified by myself, can be