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Description: 利用数据挖掘知识和vb实现K-均值聚类分析，本程序提供了训练样本和测试样本，
经过训练正确率达70-76％-Knowledge and use of data mining vb achieve K-means clustering analysis, the procedures provided training samples and test samples, after training in the correct rate of 70-76
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Size: 31744 |
Author: 111111 |
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Description: 包含两个文件KMEAN.h,KMEAN.CPP,使用方法非常简单，将数据存成.dat文件，即可对其进行Ｋ均值聚类-Consists of two documents KMEAN.h, KMEAN.CPP, very simple to use, the data saved as. Dat file can be K-means clustering
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Size: 2048 |
Author: XSSun |
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Description: k-mean算法演示，利用手工输入点通过k类自动聚合-k-mean algorithm demonstration, the use of manual input through the k-type auto-polymerization
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Size: 141312 |
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Description: k-均值聚类 小算法实例 （将8组4维数据分成6类）-k-means clustering algorithm for examples of small (to 8 Group 4 dimensional data into 6 categories)
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Size: 1024 |
Author: 姜波 |
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Description: 聚类分析算法中的最基本的K均值算法C++实现程序-Cluster analysis algorithm of the basic K-means algorithm C++ Realize procedures
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Size: 1024 |
Author: 李超 |
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Description:
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Size: 46080 |
Author: 三方 |
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Description: 神经网络的好程序，自己写的-Neural networks a good program, wrote it myself
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Size: 2048 |
Author: xiaocui |
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Description: 这是一个用Kmean处理图像的matlab文件-This is a deal with Kmean document images matlab
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Size: 1024 |
Author: bohao |
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Description: 基于k均值聚类学习算法的rbf神经网络实现-K-means clustering-based learning algorithm of rbf neural network
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Size: 1024 |
Author: 吴强 |
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Description: ddtool,实现one class classification.包括gaussian 模型， gaussian 混合模型，Parzen density，knn,kmean,kcenter等方法-ddtool, the realization of one class classification. including the Gaussian model, gaussian mixture model, Parzen density, knn, kmean, kcenter methods such as
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Size: 439296 |
Author: 何威 |
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Description: 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
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Size: 4096 |
Author: 陳志強 |
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Description: 该程序是模式识别课程里的K均值算法程序，对模式识别的进一步理解很有帮助。-The program' s curriculum are pattern recognition algorithm K-means procedure, further understanding of pattern recognition helpful.
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Size: 200704 |
Author: 何君燕 |
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Description: 模式识别中的C++源代码进行K均值法的应用-Pattern Recognition C++ source code of the application of K-means
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Size: 192512 |
Author: jacket |
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Description: 基于OpenCV的二元吗，实现了划分随机分布点集的K-均值算法。按照类别分组的输入样本顺序输出包含样本类别索引的数组labels(i)，存储在样本矩阵的第i行中。-Based on the binary OpenCV吗, implementation of the demarcation point set of randomly distributed K-means algorithm. Input in accordance with the type of packet contains samples of the output samples of the order of the array index type of labels (i), stored in the sample matrix of the first i rows.
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Size: 5120 |
Author: 无梦 |
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Description: 这是一个模式识别中的K均值算法的一个简单仿真分类实例，其中female.txt和male.txt是训练样本，test.txt是测试样本，分类效果非常好，对于模式学习的初学者将会有很大帮助。-This is a pattern recognition algorithm of the K-means classification of a simple simulation example is one of female.txt and male.txt training samples, test.txt is the measurement, classification effect is very good for beginners will be learning model has great help to me.
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Size: 2048 |
Author: 刘锐 |
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Description: 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。-k-means algorithm process as follows: First of all, the object data from the n choose k object as initial cluster centers and the remaining for the other object, then according to their cluster center with those of the similarity (distance) respectively assigned to them with the most similar (represented by cluster center) clustering obtained and then calculated for each new cluster center clustering (all objects in the cluster mean) repeated this process until the standard measure of function until the beginning of convergence.
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Size: 1024 |
Author: lining |
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Description: 这是一段MATLAB平台上的KMEAN算法，希望大家有用-Kmean
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Size: 1024 |
Author: anthony |
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Description: 一个刚编出来的K—means 聚类算法的matlab源代码 适合多维数据-Just made out of a K-means clustering algorithm matlab source code for multi-dimensional data
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Size: 1024 |
Author: 吴立锋 |
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Description: kmean algorathim implementation
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Size: 2048 |
Author: ali |
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Description: 使用k-means算法对150个数据集进行分簇。-K-means algorithm using 150 data sets to carry out sub-cluster.
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Size: 14336 |
Author: 朱东阁 |
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