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Description: 数据挖掘中的聚类算法，为k均值算法，算比较经典的算法-Clustering algorithm in data mining, considered a classic algorithm for k-means algorithm
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Size: 1024 |
Author: 周小波 |
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Description: 基于kdtree的kmeans聚类算法，在选择最近邻中心点时使用kdtree的检索功能，提高了检索效率，特别是当k较大时，效果明显提升-kmeans clustering algorithm based on kdtree，used in selecting the center point of the nearest neighbor the kdtree retrieval function, and improve the retrieval efficiency has improved significantly, especially when k is larg
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Size: 22528 |
Author: shiyulong |
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Description: 基于LK光流算法的人体检测及Kmeans方法进行聚类-human detection based on LK optical algorithem
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Size: 1024 |
Author: mengyang |
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Description: 2D-Kmeans clustering algorithm. It can be used for audio(source localization) and image clutstering(object clustering in an image)-2D-Kmeans clustering algorithm. It can be used for audio(source localization) and image clutstering(object clustering in an image)..
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Size: 1024 |
Author: venkatesh |
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Description: 采用快速K近邻与Kmeans聚类算法来计算前K个近邻，舍弃了一部分不可能成为待测样本的前K个近邻的训练样本，从而减少了计算量，提高了分类速度-Fast K-nearest neighbor Kmeans clustering algorithm to calculate the K nearest neighbors, abandoning the training samples of the part can not become the first K neighbors of the test sample, thereby reducing the amount of calculation and improve the speed of classification
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Size: 4096 |
Author: houying |
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Description: 文本聚类及主题挖掘相关论文合集，包括了kmeans，层次聚类，ap聚类等等相关方法-Text clustering and topic mining related collection of papers
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Size: 22890496 |
Author: lyh |
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Description: k-means算法，将图像元素剥离显示出来-K- means algorithm, spin out the image element is displayed
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Size: 1024 |
Author: 王力 |
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Description: 用java实现的K-Means算法，里面主要是一个具体实现的例子。-An example of K-Means algorithm implemented by java language.
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Size: 5120 |
Author: 盛权 |
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Description: Nous avons effectué les tests en tenant compte
des paramètres utilisés afin de mettre en évidence leur
influence. Sur les deux images testées, nous avons
constaté que l’espace colorimétrique utilisé pour
calculer la différence colorimétrique entre deux
régions (RVB ou L
*
a
*
b
*
) ainsi que le mode de
segmentation (progressive ou par priorité) influent sur
les résultats de segmentation. Nous avons mis aussi en
évidence l’importance du seuil, qui est décisif sur les
résultats que l’en veut atteindre. Nous pouvons
également con
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Size: 2048 |
Author: tunisia |
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Description: 运用谱聚类——Ncuts和NJW的算法结合kmeans进行了聚类分析-Using spectral clustering- Ncuts and NJW algorithm combining kmeans clustering analyzed
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Size: 10240 |
Author: 李晶 |
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Description: Image processing for segmentation using Kmean algorithm
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Size: 1024 |
Author: lalainany |
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Description: MRI 脑组织参数估计与分割。此程序用两种方法——Kmeans和期望最大化EM对比对MRI脑组织进行分割和参数估计-The MRI parameter estimation and segmentation of brain tissue. This program on MRI brain tissue segmentation and parameter estimation using two methods-- Kmeans and expectation maximization EM contrast
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Size: 81920 |
Author: 冯娇 |
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Description: 本代码提供了K-means聚类算法的一个C语言实现，希望可以为学习聚类算法的朋友提供一些帮助。-This code provides a K-means clustering algorithm C language, and hope to provide some help for friends learning clustering algorithm.
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Size: 1024 |
Author: Bill |
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Description: java实现kmeans算法，可以处理任意维度的向量。并将聚类结果写入文本。-The kmeans algorithm java, and can handle any dimension vector. And write text clustering results.
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Size: 693248 |
Author: 武夷河 |
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Description: 字符识别的特征提取，内附有处理前的数据和处理后的数据，解压后即可使用-Character recognition feature extraction, enclosed is the manipulation of data from the data before and after treatment, after decompression can be used
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Size: 2048 |
Author: 婉儿 |
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Description: k均值聚类算法，可以有效的找到聚类中心，并且把两类聚在一起，很经典实用。-k-means clustering algorithm, can effectively find the cluster center, and the two categories together, very classic.
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Size: 1024 |
Author: peter |
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Description: 输入：聚类个数k，以及包含 n个数据对象的数据库。输出：满足方差最小标准的k个聚类。处理流程： （1）从 n个数据对象任意选择 k 个对象作为初始聚类中心.
（2）根据每个聚类对象的均值（中心对象），计算每个对象与这些中心对象的距离；并根据最小距离重新对相应对象进行划分；（3）重新计算每个（有变化）聚类的均值（中心对象）
（4）循环（2）到（3）直到每个聚类不再发生变化为止-Input: number of clusters k, and n data object contains a database. Output: meet the standard minimum variance k-clustering. Processes: (1) n data objects from arbitrarily selected k object as initial cluster centers. (2) based on the mean of each cluster object (central object), calculated for each object and the distance to the object of these centers and according to the minimum distance to re-divide the corresponding object (3) re-calculated for each (a change) clustering means (central object) (4) Cycle (2) to (3) until no further change in each cluster until the
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Size: 2048 |
Author: liyu |
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Description: kmeans dataset iris.dat
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Size: 1024 |
Author: dalvit |
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Description: kmeans程序，中有小例子，简单实现的小程序-kmeans program, there is a small example, a simple small program to achieve
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Size: 7650304 |
Author: xuelu |
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Description: 自己写的kmeans聚类并消除异常点的matlab代码。-kmeans clustering matlab code with outliers eliminate.
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Size: 1024 |
Author: tangweicheng |
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