文件名称:Density-ratio-based-clustering-master
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相比其他的聚类方法，基于密度的聚类方法可以在有噪音的数据中发现各种形状和各种大小的簇。DBSCAN（Ester, 1996）是该类方法中最典型的代表算法之一（DBSCAN获得2014 SIGKDD Test of Time Award）。其核心思想就是先发现密度较高的点，然后把相近的高密度点逐步都连成一片，进而生成各种簇(Compared with other clustering methods, the density based clustering method can find various shapes and sizes of clusters in noisy data. DBSCAN (Ester, 1996) is one of the most typical representation algorithms in this kind of method (DBSCAN obtains 2014 SIGKDD Test of Time Award). The core idea is to find a point with higher density, and then gradually connect the similar high density points to a variety of clusters.)
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下载文件列表
| 文件名 | 大小 | 更新时间 |
|---|---|---|
| Density-ratio-based-clustering-master | 0 | 2016-09-14 |
| Density-ratio-based-clustering-master\Data | 0 | 2016-09-14 |
| Density-ratio-based-clustering-master\Data\hard.mat | 33032 | 2016-09-14 |
| Density-ratio-based-clustering-master\Data\s1.mat | 13843 | 2016-09-14 |
| Density-ratio-based-clustering-master\Data\s2.mat | 22860 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies | 0 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\DRSCAN.m | 1840 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\FmeasOPTICS.m | 1480 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\MSNN.m | 1063 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\Mdbscan.m | 2081 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\Moptics.m | 2518 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\ReConOPTICS.m | 6922 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\Rescale.m | 744 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\SNN.m | 904 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\cluster_optics.m | 7140 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\ds2nfu.m | 3049 | 2016-09-14 |
| Density-ratio-based-clustering-master\Dependancies\optics.m | 2660 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations | 0 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\Fmean.m | 868 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\Fmean2.m | 947 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\ProduceMatrix.m | 740 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\accuracy.m | 875 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\adjrand.m | 942 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\euclidean.m | 1341 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\evaluate.m | 1778 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\hungarian.m | 9229 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\nmi.m | 1750 | 2016-09-14 |
| Density-ratio-based-clustering-master\Evaluations\normalize.m | 331 | 2016-09-14 |
| Density-ratio-based-clustering-master\VisualiseReScale.m | 1652 | 2016-09-14 |
| Density-ratio-based-clustering-master\readme.txt | 3380 | 2016-09-14 |
| Density-ratio-based-clustering-master\testReCon.m | 1882 | 2016-09-14 |
| Density-ratio-based-clustering-master\testRescale.m | 1964 | 2016-09-14 |