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- k-means 算法接受参数 k ；然后将事先输入的n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。-k-means algorithm accepts parameters k n and the previously input data is divided into k-clustering objects in order to make
important2
- 基于聚类的径向基神经网络的设计算法，采用的是K均值聚类。实现函数拟合！-The design algorithm of radial basis function neural network based on clustering, using the K mean clustering. Realize the function fitting!
gerbil-1.0b-win-x64
- image segmentation with k-means algorithm and mean shift clustering and filtering
background-model3
- 针对背景差法易受外界环境因素影响的缺点, 提出了一种基于改进K-均值聚类的背景建模方法。通过比较任意样本与该像素位置处的子类中心之间的距离, 对各个像素的观察值进行聚类, 并在聚类过程中逐步确定其类别数。一段时间的学习之后, 样本数最多的子类就构成了背景模型。仿真结果表明, 该算法即使在运动目标存在的情况下也能准确的提取出实际的 背景, 而且显著地降低了系统的存储量。-Aimed at the disadvantage that background subtraction was liab
FCM
- 自己实现的，模糊C均值聚类的代码，在K-mean上添加了隶属度矩阵。注释详细，方便理解算法步骤-my implementation, Fuzzy C-Means clustering code in the K-mean adding a membership matrix. Notes detailed, easy to understand algorithm steps
K_Means
- k-means 算法的工作过程说明如下：首先从n个数据对象任意选择 k 个对象作为初始聚类中心；而对于所剩下其它对象，则根据它们与这些聚类中心的相似度（距离），分别将它们分配给与其最相似的（聚类中心所代表的）聚类；然后再计算每个所获新聚类的聚类中心（该聚类中所有对象的均值）；不断重复这一过程直到标准测度函数开始收敛为止。一般都采用均方差作为标准测度函数. k个聚类具有以下特点：各聚类本身尽可能的紧凑，而各聚类之间尽可能的分开。下面给出我写的源代码。-work process k-means al
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!
kmeanhar
- a simple yet effective code for k mean clustering algorithm
Kmeans
- k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。-k-means algorithm accepts input k then n data objects into k clusters in order to make clustering satisfy obtained: the objects i
kMeansCluster
- k-Means 算法接受输入量 k ；然后将 n 个数据对象划分为 k 个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个 “ 中心对象 ” （引力中心）来进行计算的。-K-Means algorithm accepts input amount of K then the object n data is divided into k cluster so that the obtained clusteri
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
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
adfagf
- K-均值类算法的matlab源码，很实用，注解详细-K- mean class algorithm matlab source code, very practical, detailed notes
Kmeans-and-PCA
- K—mean分类和主成分分析法的应用实例，很明晰的讲解实例，非常适合算法应用的学习-Application examples Kmean classification and principal component analysis, it is clear to explain instance, very suitable learning algorithm
K_Mean
- K_Mean聚类分析算法用于各地区城镇居民年人均收入的分析（分别4类），包括原始数据以及代码！结果在Data1、Data2、Data3、Data4中.-K Mean clustering algorithm used to analyze the regional urban residents per capita income (Class 4, respectively), including the original data and code! Result in Data1, Dat
AIS
- 船舶AIS轨迹提取，作出船舶AIS轨迹图。在此基础上，实现基于空间相似距离的K均值轨迹聚类。算法可以自定义轨迹聚类初始轨迹或者由程序随机生成初始轨迹，采用迭代的方法直到确定最终的聚类中心。-The extraction of ship AIS trajectory, make ship AIS trajectories. On this basis, to achieve similar K mean trajectory clustering based on distance space.
Kmean
- k-mean聚类算法。最简实现，全部做了中文注释-K-mean clustering algorithm. The simplest implementation, all done in Chinese Notes
kmeans
- 可以直接拿来用 python2.7 在数据挖掘中，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。(In the data mining, K-Means algorithm is a cluster analysis algorithm, which is mainly to calculate the data aggregation algorithm, mainly through the con
Speech Processing Analysis - MATLAB
- The number of states in GMM as the generative model of the frames is obtained using k-means algorithm. This also helps to initialize the mean vector and the covariance matrix of the individual state of the GMM. The training LPC frames collected fro