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. Platform: |
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Author:韩磊 |
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Description: 采用C++语言编写的，用于聚类相关方面的dbscan算法源程序，希望大家共同提高-using the C language for the relevant aspects of clustering algorithm source dbscan hope that we can raise! ! Platform: |
Size: 123904 |
Author:周君 |
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Description: 这个是K-Means动态聚类算法的源程序，需要的请下，请多多指教，谢谢！-This is a K- Means clustering algorithm source, the need to please, please exhibitions, thank you! Platform: |
Size: 32768 |
Author:HaicoLi |
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Description: DBSCAN源代码,是一种典型的基于密度的聚类算法-DBSCAN source code, is a typical example of the density-based clustering algorithm Platform: |
Size: 9216 |
Author:龙卑鄙 |
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Description: 程序说明：
Form1.cs是应用聚类算法DBSCAN (Density-Based Spatical Clustering of Application with Noise)的示例，可以通过两个参数EPS和MinPts调节聚类。
DBSCAN.cs是实现文件，聚类算法的进一步信息请参考“数据挖掘”或者相关书籍
聚类示例数据来自于sxdb.mdb，一个Access数据库。
已知问题及进一步改进建议：
问题：dbscan.cs行64，SortedList不支持重复键，因此若两个数据点距离相同则无法加入集合
解决：采用人为减小一个微小量，使数据点距离不同且不影响聚类结果
上一解决方案的问题：减小double.Epsilon微小量无助于使SortedList认为两点距离以及不同
解决：采用一个指数增长的微小量，连续重试直至SortedList认为距离已经不同
进一步改进建议：可能通过double的强制转型为内存中的byte类型（假设double型转为8个byte）
然后最后一个byte减去0x01可比较漂亮的解决问题，但是……呵呵，C#中我不会这个操作
也可以自己实现一个SortedList，支持重复键，当然，这，好像是微软应该做的工作了 ^_^
Eric Guo
<http://www.cnblogs.com/ericguo/>
-procedures : Form1.cs clustering algorithm is applied DBSCAN (Density-Based Spati cal Clustering of Application with Noise) example, two parameters can EPS and MinPts regulation clustering. DBSCAN.cs is, the clustering algorithm further information please refer to the "data mining" or books related data clustering example from sxdb.m db, an Access database. Known issues and recommendations for further improvement : : 64 dbscan.cs OK, SortedList not support duplicate keys, and therefore if two data points from the same pool can not be solved by adding : By applying an artificially reduce a small amount of data from different points without clustering results on the impact of a solution of the problem : double.Epsilon small decrease in the amount of helplessness to make that 2:00 S Platform: |
Size: 26624 |
Author:Huang Yi |
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Description: 聚类算法的vc++代码实现，包含了两种算法-clustering algorithm to achieve the vc code, includes two algorithms Platform: |
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Author:liu yang |
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Description: 经典cure聚类算法,实现用c++语言.大家-classic cure clustering algorithm, and using the c language. We look at Platform: |
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Author:孔明 |
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Description: DGCL （An Efficient Density and Grid Based Clustering Algorithm for Large Spatial Database）的实现代码，费了很长时间才实现的-DGCL (An Efficient Density and Grid Based C. lustering Algorithm for Large Spatial Databas e) the realization of code, and a very long time to achieve the Platform: |
Size: 2092032 |
Author:adrian |
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Description: 本文目前模糊C-均值聚类算法不适用于有噪声和样本不均衡等问题,借助改进算法AFCM和WFCM的思想,提出另一种新的聚类算法。它是AFCM和WAFCM结合的一种算法,但有着更好的健壮性和聚类效果。-This article is currently fuzzy C-means clustering algorithm is not applicable to samples of noise and uneven and so on, with improved algorithm AFCM and WFCM ideas, put forward a new clustering algorithm. It is a combination of AFCM and WAFCM an algorithm, but has better robustness and clustering effect. Platform: |
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Author:guoguo |
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Description: DBSCAN是一个基于密度的聚类算法。改算法将具有足够高度的区域划分为簇，并可以在带有“噪声”的空间数据库中发现任意形状的聚类。-DBSCAN is a density-based clustering algorithm. Algorithm change will have enough height to the regional cluster. and to be with the "noise" of the spatial database found clusters of arbitrary shape.-DBSCAN is a density-based clustering algorithm. Changed algorithm will have a high enough regional divided into clusters, and to be with noise found in the spatial database cluster of arbitrary shape.-DBSCAN is a density-based clustering algorithm. Algorithm change will have enough height to the regional cluster. And to be with the noise of the spatial database found clusters of arbitrary shape. Platform: |
Size: 24576 |
Author:蔡宗欣 |
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Description: c-mean聚类算法源代码，通过对输入数据进行训练和分类类别设定，能够得到数据的聚类图。-c-mean clustering algorithm source code, through the input data for training and classification of types of settings can be data clustering Fig. Platform: |
Size: 2048 |
Author:张红 |
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Description: 经典的层次聚类算法Birch。在linux下运行通过，可以实现大规模数据的层次聚类。-Classical hierarchical clustering algorithm Birch. In linux run through, you can realize a large-scale data on hierarchical clustering. Platform: |
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Author:肖宪 |
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Description: 使用c-均值聚类算法在IRIS数据上进行聚类分析，随机选择三个初始聚类中心，经过多次迭代，最终将150个样本分为三类。-Use c-means clustering algorithm in the IRIS data on the cluster analysis, three randomly chosen initial cluster centers, through a series of iterative, 150 samples will eventually fall into three categories. Platform: |
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Author:liz |
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Description: CURE: AN EFFICIENT CLUSTERING ALGORITHM FOR LARGE DATABASES-CURE: AN EFFICIENT CLUSTERING ALGORITHM FOR LARGE DATABASES Platform: |
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