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Description: k均值聚类算法分析，采用C++编程技术，提供代码可重用机制 -k-means clustering algorithm analysis, the use of C programming, code reuse mechanism
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Size: 31002 |
Author: chu na |
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Description: K均值聚类算法源代码-K-means clustering algorithm source code
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Size: 30395 |
Author: 静子 |
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Description: 对图像进行K均值聚类的程序
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Size: 179761 |
Author: gunner |
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Description: K-均值聚类算法的matlab源程序，K-均值聚类算法的matlab源程序
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Size: 2434 |
Author: whitter |
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Description: K均值聚类算法源代码-K-means clustering algorithm source code
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Size: 29696 |
Author: 静子 |
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Description: k均值算法的源代码-k means algorithm source code
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Size: 2048 |
Author: 刘新华 |
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Description: K-均值聚类算法的编程实现。包括逐点聚类和批处理聚类。K－均值聚类的的时间复杂度是n*k*m，其中n为样本数，k为类别数，m为样本维数。这个时间复杂度是相当客观的。因为如果用每秒10亿次的计算机对50个样本采用穷举法分两类，寻找最优，列举一遍约66.7天，分成3类，则要约3500万年。针对算法局部最优的缺点，本人正在编制模拟退火程序进行改进。希望及早奉给大家，倾听高手教诲。-K-means clustering algorithm programming. Point by point, including clustering and clustering batch. K-means clustering of the time complexity of n* k* m, n samples, several types of k, m sample dimension. The time complexity is a very objective. Because if we use one billion times per second the computer using 50 samples of two exhaustive method to find the optimal set out again about 66.7 days, divided into three categories, offering 3,500 years. Local optimal algorithm against the shortcomings, I was prepared simulated annealing process improvements. Early Feng hope for everyone, listen to the master teachings.
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Size: 4096 |
Author: 韩磊 |
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Description: 由于K－均值聚类算法局部最优的特点，而模拟退火算法理论上具有全局最优的特点。因此，用模拟退火算法对聚类进行了改进。20组聚类仿真表明，平均每次对K结果值改进8次左右，效果显著。下一步工作：实际上在高温区随机生成邻域是个组合爆炸问题（见本人上载软件‘k－均值聚类算法’所述），高温跳出局部解的概率几乎为0，因此正考虑采用凸包约束进行模拟聚类，相关工作正在进行。很快将奉献给各位朋友。-as K-means clustering algorithm for optimal local characteristics, and simulated annealing algorithm theory with the characteristics of the global optimum. Thus, simulated annealing algorithm for clustering improvements. Cluster Group of 20 simulations show that the average value of K results improved about eight times, the results are obvious. The next step : In fact, in high temperature generated random neighborhood is a combination of explosives (see my software on the 'k-means clustering algorithm' mentioned above), high-temperature solution of partial out almost zero probability, it is considering the use of convex hull bound for simulation cluster, the work under way . Soon dedication to the ladies.
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Size: 5120 |
Author: 韩磊 |
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Description: k均值聚类算法源码，比较经典，无解压密码-kmeans clustering algorithm source code,comparatively classical,no password for unzip
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Size: 29696 |
Author: 司南 |
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Description: 这是K均值聚类算法的程序,应用相当广泛的,比如在模式识别里就很重要.-This is the K-means clustering algorithm, application fairly extensive, such as pattern recognition is important to Lane.
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Size: 214016 |
Author: fun |
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Description: 这是用C++作的K-均值聚类算法，模式识别当面的，希望对大家有所帮助！-C is for the K-means clustering algorithm, pattern recognition face-to-face, we want to help!
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Size: 4096 |
Author: Jesson |
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Description: k均值聚类算法分析，采用C++编程技术，提供代码可重用机制 -k-means clustering algorithm analysis, the use of C programming, code reuse mechanism
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Size: 30720 |
Author: chu na |
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Description: 模糊k均值聚类算法,一种在数据挖掘中聚类大型分类数据集的快速聚类方法-fuzzy k-means clustering algorithm, a data mining classification clustering large data sets quickly clustering method
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Size: 102400 |
Author: 路虎 |
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Description: k均值聚类算法源码
聚类算法学习的实例功能-k-means cluster algorithm
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Size: 3072 |
Author: wueching |
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Description: K均值聚类算法图像分割，最传统的一种分割方法(K mean clustering segmentation)
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Size: 13312 |
Author: 瞌睡虫醒了呀
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Description: 介绍了传统的图像分割与K-均值聚类算法分割，然后利用OpenCV函数将其实现，并介绍了OpenCV中图像分割相关的基本函数。(This paper introduces the segmentation of traditional image segmentation and K- mean clustering algorithm, then uses OpenCV function to implement it, and introduces the basic functions of image segmentation in OpenCV.)
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Size: 464896 |
Author: 术道
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Description: 用VC++写的K均值聚类算法，可以直接使用(K mean clustering algorithm is written by VC++ , which can be used directly.)
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Size: 187392 |
Author: gongshixin
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Description: 根据k均值聚类的原理，实现一些数字的聚类，但是具体类别数需要自己设置(Clustering of some numbers by K mean clustering)
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Size: 2109440 |
Author: fighter小皮皮 |
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Description: K均值聚类算法-对数据进行聚类分析，适合数据处理(k means clustering algorithm)
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Size: 3072 |
Author: 季jsx |
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