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Description: Test k-means on 2-D data
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Size: 2048 |
Author: 黎思 |
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Description: 用得最多的是最近邻，此处上传的是K-近邻，即k＝1。matlab环境下的代码。附有实例。-used most often is the nearest neighbor, here is uploaded K-neighbor, k = 1. Matlab environment code. With examples.
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Size: 1024 |
Author: 宋争鸣 |
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Description: 快速k-means算法，比matlab 自带的要快很多。-rapid k-means algorithm, compared to the Matlab bringing their much faster.
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Size: 3072 |
Author: zhang chun xiao |
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Description: k-means som 层次聚类
算法比较-k-means clustering algorithm level som comparison
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Size: 110592 |
Author: niyang |
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Description: 这是一个用c和matlab编写的程序，用于实现k-means算法-This is a matlab with c and the preparation of the procedures used to implement k-means algorithm
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Size: 6144 |
Author: 海天 |
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Description: K均值聚类算法,matlab编写,很好用-K means clustering algorithm, matlab prepared very well with
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Size: 2048 |
Author: 桂长青 |
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Description: How the K-mean Cluster work
Step 1. Begin with a decision the value of k = number of clusters
Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following:
Take the first k training sample as single-element clusters
Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster.
Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample.
Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. -How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
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Size: 2048 |
Author: yangdi |
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Description: K-MEANS算法程序(MATLAB环境)-K-MEANS algorithm procedure (MATLAB environment)
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Size: 1024 |
Author: liuwei |
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Description: k-均值算法 做的图象分割实例 （将图片像素聚成三类）-k-means algorithm to do the image segmentation example (poly-pixel pictures into three categories)
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Size: 104448 |
Author: 姜波 |
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Description: 改进的k均值算法，可以加速运行时间，详见Using the Triangle Inequality to Accelerate k-Means-Improved k-means algorithm, can accelerate the running time, see Using the Triangle Inequality to Accelerate k-Means
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Size: 13312 |
Author: xz |
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Description: k均值聚类的动态分类算法 灰度图和彩图的
-k-means clustering algorithm for the dynamic classification of grayscale and color
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Size: 3072 |
Author: zhangyan |
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Description: k-means聚类算法，并用遗传算法辅助实现聚类的实现。-k-means clustering algorithm, and genetic algorithm-assisted clustering realize realize.
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Size: 1024 |
Author: ginger |
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Description: K均值聚类算法，将模式识别方法与图像处理技术相结合，掌握利用K均值聚类算法进行图像分类的基本方法-K-means clustering algorithm, the pattern recognition method and image processing technology, to master the use of K-means clustering algorithm is the basic method of image classification
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Size: 1024 |
Author: 孟星 |
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Description: k均值算法matlab实现，模式识别中常用-k-means algorithm matlab realize, pattern recognition used in
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Size: 1024 |
Author: chenyu |
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Description: k-均值聚类算法实现灰度图像分割，输入图像矩阵和聚类中心个数，返回为最终的聚类中心和图像中每个像素所属类的编号（对应于图像矩阵）-k-means clustering algorithm to achieve gray-scale image segmentation, the input image matrix and the number of cluster centers, the return for the final image of the cluster centers and their respective categories in each pixel number (corresponding to the image matrix)
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Size: 1024 |
Author: cc |
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Description: K-MEANS聚类算法，以及PSO和QPSO算法改进K-MEANS算法，breastcancer数据验证了该分类模型的有效性-K-MEANS clustering algorithm, and the PSO algorithm and QPSO to improve K-MEANS algorithm, breastcancer data verified the validity of the classification model
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Size: 43008 |
Author: 李慧 |
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Description: cskmeans 聚类算法的一种
1. 分裂法(partitioning methods)：给定一个有N个元组或者纪录的数据集，分裂法将构造K个分组，每一个分组就代表一个聚类，K<N。而且这K个分组满足下列条件：（1） 每一个分组至少包含一个数据纪录；（2）每一个数据纪录属于且仅属于一个分组（注意：这个要求在某些模糊聚类算法中可以放宽）；对于给定的K，算法首先给出一个初始的分组方法，以后通过反复迭代的方法改变分组，使得每一次改进之后的分组方案都较前一次好，而所谓好的标准就是：同一分组中的记录越近越好，而不同分组中的纪录越远越好。使用这个基本思想的算法有：K-MEANS算法、K-MEDOIDS算法、CLARANS算法；
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Size: 1024 |
Author: lance |
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Description: K均值算法支持向量机,很使用可靠,看了一定不会后悔的-K-means algorithm for support vector machines, it is the use of reliable, read will not regret it
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Size: 53248 |
Author: 刘期烈 |
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Description: matlab源码关于模糊K均值聚类算法，很好的，适合大家下载研究学习-matlab source code on the fuzzy K-means clustering algorithm, very good for everyone to download research study
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Size: 1024 |
Author: 亨利 |
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Description: 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。
Matlab 源代码，以兰花数据集作为测试对象。-k-means algorithm to accept input k then n data object is divided into k-clustering in order to make available to the cluster to meet: the same objects in clustering high similarity and objects in different clustering the similarity smaller. Cluster similarity is the use of the clustering of objects by means of a
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Size: 3072 |
Author: 烈马 |
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