搜索资源列表
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!
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
kmeans
- k means clustering algorithm used for clustering a spread data
dctconfig
- K-means clustering is a key technique in pixel-based methods. Because pixel-based methods based on Kmeans clustering are simple and the computational complexity is relatively low compared with other
kMeansProjectiveClustering
- kmeans clustering genetic algorithms
FastKmeansSourceCodeCpp
- 快速K-Means聚类：ENNS PDS 添加到搜索过程中，速度降至FS的10 左右-Fast K-Means Clustering: ENNS PDS to the search process
Kmeans
- a kmean clustering prog
kMeansCluster
- 采用kmeans聚类方法，实现多个配送中心选址。-By kmeans clustering method of multiple distribution center location.
accord-kmeans-source
- K-Mean clustering source code
matlab---Kmeans
- kmeans聚类算法，比较经典的算法，里面有讲解，容易理解-kmeans clustering algorithm to compare the classical algorithm, which has to explain, easy to understand
kmeans
- kmeans聚类，c++源代码，任意中心点选择，迭代到收敛-kmeans clustering
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!
Kmeans-Clustering
- K-均值聚类的代码，可是将数据改一下直接用。-The code of Keans Clustering
K-means-master
- KMEans Clustering Algorithm
Kmeans
- 采用C#语言完成了Kmeans 聚类算法的聚类过程。(The clustering process of Kmeans clustering algorithm is completed by C# language.)
accord-machinelearning-clustering-(k-means)
- Accord.NET环境下的Kmeans聚类实例。(Kmeans clustering example under the Accord.NET environment.)
Kmeans
- 一个matlab的kmeans聚类算法代码，输入聚类数据和类簇数，输出分好类的数据(A matlab kmeans clustering algorithm code, input cluster data and cluster number, the output of the good class of data)
EM_KMeans_Algorithm(1)
- source code of kmeans clustering in matlab
kmeans
- kmeans聚类代码，对给定数据集进行聚类处理(Clustering code to cluster a given data set)
Clustering
- 1) 使用凝聚型层次聚类算法（即最小生成树算法）对所有数据点进行聚类，最后聚成3类。相异度定义方法可选择single linkage、complete linkage、average linkage或者average group linkage中任意一种。 2) 使用C-Means算法对所有数据点进行聚类。C=3。 任务2（必做）： 使用高斯混合模型（GMM）聚类算法对所有数据点进行聚类。C=3。并请给出得到的混合模型参数（包括比例??、均值??和协方差Σ）。 任务3（全做）： 1) 参考数据文