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K-means-clustering-algorithm
- K均值聚类算法-适用于裁判打分等经典分类，适合初学者-K-means clustering algorithm- classical classification applies to the referee scoring for beginners
K
- 这是K均值聚类的程序，数据挖掘等课程都需要-This is a K-means clustering procedures, data mining courses
k-mean
- k—均值分割，分割效果明显，在Matlab下完美实现-K-segmentation, segmentation obviously perfect realization in Matlab
k-means
- k-均值聚类算法C语言源码,k-均值聚类算法C语言源码-k-means clustering algorithm C language source code
K-means
- 调用GDAL库实现模式识别的K均值和ISODATA算法，对图像的分类-Call GDAL library implementation of K-means and ISODATA algorithms pattern recognition, image classification
k-means
- 对于模式识别分类，利用K均值聚类，对原始数据进行分类。比较易于收敛，十分好用-For pattern recognition classification using the K-means clustering, and classification of the original data. Relatively easy to convergence, very easy to use
K-means
- K均值聚类的例子程序，程序中有附带的数据-examples of k-means technology
k-mean-sift
- K均值分割 在图像角点提取中使用 使用VC++进行的编程-K-means segmentation the image corner extraction using VC++ carried programming
k-means-for-image-segmentation
- k均值用于图像分割，对于相同颜色但深度不一样可以分割。-k-means for image segmentation, the same color depth can be split.
K-means
- K均值算法描述： 给定类的个数K，将N个对象分到K个类中去， 使得类内对象之间的相似性最大，而类之间的相似性最小。-K-means algorithm described: a given number of classes K and N objects assigned to the K-th class, so that objects within the class of the similarity between the maximum, while the simi
K-means-color-segmentation
- K均值图像检测，GUI界面，可对彩色图像分割-K-means image detection, the GUI interface, color image segmentation
K-MEANS
- k均值聚类是最著名的划分聚类算法，由于简洁和效率使得他成为所有聚类算法中最广泛使用的。给定一个数据点集合和需要的聚类数目k，k由用户指定，k均值算法根据某个距离函数反复把数据分入k个聚类中。-k-means clustering is one of the most famous partition clustering algorithm, due to the simplicity and efficiency so that he became the most widely used i
k-means
- k—均值算法opencv代码实现。 k-Means 算法是一种 cluster analysis 的算法，其主要是来计算数据聚集的算法，主要通过不断地取离种子点最近均值的算法。
K-mean
- K均值聚类,用于空间区域的自适应划分，用MATLAB软件来实现。-K-means clustering for adaptive division of the region of space, using MATLAB software to achieve.
K-means-clustering-algorithm
- K均值算法使用的聚类准则函数的误差平方和准则，通过反复迭代优化聚类结果，使所有样本到各自所属类别的中心的距离平方和达到最小。-K-means clustering algorithm uses squared error criterion function and criteria through iterative optimization clustering result, all the samples to the respective classes of the center s
K-Means
- 数据挖掘中的K-均值聚类算法，java语言实现。 可直接编译运行-Data Mining K-means clustering algorithm, java language.
K-means-
- 一种基于颜色的分割，使用聚类算法中的K均值算法。本例主要用到的函数是色彩空间转换函数makecform和applycform，对于K均值聚类使用kmeans函数。-Based on color segmentation, using clustering algorithm K-means algorithm. In this case the main function used is the color space conversion function makecform and appl
k
- k均值算法，数据挖掘里面比较基础的算法，实现类聚-k-means algorithm, which based on the comparison of data mining algorithms to achieve clustering
k-mean
- K均值（用matlab实现花的分类，附注释，程序简单）-K-means (machine learning job classification flowers)
K-maens
- K均值聚类算法对图像进行分割，实验用程序，亲测可用。-K-means clustering algorithm for image segmentation, experimental procedures, pro-test is available.