搜索资源列表
K-Mean聚类算法
- 本程序是基于vc++实现K-Mean聚类
K-均值聚类算法
- K-均值聚类算法，对数据进行聚类分析，可用于提取关键帧等。用matlab实现,K-means clustering algorithm, cluster analysis of data that can be used, such as key frame extraction. Using matlab to achieve
K-mean-clustering
- K-mean方法聚类 实现多幅图像的K均值方法的聚类并显示-K-mean clustering，Efficient method to achieve multiple images of the K-means clustering method and display
textureseg
- 用多尺度Gabor小波滤波器组实现纹理分割，其中聚类算法采用K均值聚类，本科毕业设计，省优秀-multi-scale Gabor wavelet，texture segmentation，k-mean clustering
k-rbf
- 程序是基于K均值聚类的RBF代码，很好的一个例子。-K means clustering procedure is based on the RBF code, a good example.
K-Means
- K均值聚类算法 C++实现的K均值聚类算法。-K means clustering algorithm C++ Achieved K-means clustering algorithm.
kMean
- clustering的经典k-mean算法源程序，VB代码-clustering k-mean algorithm, in VB
k-mean k均值聚类程序
- k均值聚类程序，虽然matlab中也有自带的，但是这个速度不错。-program for k means used for cluster
k-meams(sourcecode)
- C#实现k均值文本聚类算法，文本聚类C#源程序，k-means聚类算法-C# to achieve k means clustering algorithm, document clustering C# source code, k-means clustering algorithm
K-Mean
- 遥感影像K均值分类算法，针对bmp彩色图像。VC++6.0编程实现。-K means of remote sensing image classification algorithm for bmp color images. VC++6.0 programming.
K-mean聚类的原理和MapReduce实现
- K-mean聚类的原理和MapReduce实现
K-MEANS
- 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-watershed segmentation on matlab
K-means
- 模式识别 k-mean算法程序，用Visual c++编写-K-mean algorithm for pattern recognition procedures, using Visual c++ Prepared
Kmean
- 自行implement的k-mean(含fuzzy c mean)，可以直接於vc++針對大量數據進行分群的動作-Implement on its own the k-mean (with fuzzy c mean), can be directly in vc++ For clustering large amount of data movement
K-Means.Algorithm
- 算法，k-mean搜索方法，执行起来很快，推荐。-Algorithm, k-mean search methods, to implement quickly, recommended.
K-means.m
- K-mean均值算法的matlab功能实现-K-means to achieve the matlab function
K-Mean
- K-mean 算法 用Java实现的算法 从别人那看的 -k-mean
K-mean
- 基于纹理度量的图像分割，适用于遥感图像，主要利用到K-mean算法。-Image segmentation based on texture measurement for remote sensing image, the main advantage of K-mean algorithm.
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-mean+k-medoids
- 机器学习中的两个基本算法，k-means 和k-medoids 通过学习英文课件，更好的理解算法内涵(Machine learning in the two basic algorithms, K-means and k-medoids through learning English courseware, better understanding of the algorithm connotation)