Description: 二维的DBSCAN聚类算法，输入（x,y）数组，搜索半径Eps，密度搜索参数Minpts。输出: Clusters，每一行代表一个簇，形式为簇的对象对应的原数据集的ID-two-dimensional clustering algorithm, the input (x, y) array, search radius Eps. Minpts density search parameters. Output : Clusters, each firm on behalf of a cluster, in the form of clusters of objects corresponding to the original data set ID Platform: |
Size: 1024 |
Author:胡瑞飞 |
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Description: 这是一种基于密度的聚类分析算法，可以发现任意形状的簇，可以发现噪声点。-This is a density-based clustering analysis algorithm can find clusters of arbitrary shape can be found noise points. Platform: |
Size: 2048 |
Author:dys |
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Description: ：DBSCAN是一个基于密度的聚类算法。该算法将具有足够高密度的区域划分为簇，并可以在带有“噪声”的空间数
据库中发现任意形状的聚类。但DtLqCAN算法没有考虑非空间属性，且DBSCAN算法需扫描空间数据库中每个点的e一
邻域来寻找聚类，这使得DBSCAN算法的应用受到了一定的局限。文中提出了一种基于DBSCAN的算法，可以处理非空
间属性，同时又可以加快聚类的速度。-: DBSCAN is a density-based clustering algorithm. The algorithm has a sufficiently high density area is divided into clusters, and to be with the " noise" found in the spatial database clusters of arbitrary shape. But DtLqCAN algorithm did not consider non-spatial attributes, and spatial database DBSCAN algorithm to be scanned for each point e in the neighborhood to find a cluster, DBSCAN algorithm which makes the application subject to certain limitations. In this paper, an algorithm based on DBSCAN can handle the non-spatial attributes, can also speed up the clustering speed. Platform: |
Size: 215040 |
Author:sdc |
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Description: matlab 实现基于dbdcan的聚类算法，帮你在matlab中简易的实现了解- it helps you study cluster alogroim in the matlab Platform: |
Size: 6144 |
Author:feimeng |
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Description: dbscan算法，数据挖掘期末作业。用matlab编写。自己是一份报告。内含全部代码。测试可以使用。-dbscan algorithms, data mining final assignment. Written in matlab. It is a report. Contains all the code. Test can be used. Platform: |
Size: 30720 |
Author:许鑫 |
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Description: 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.) Platform: |
Size: 95232 |
Author:zkzfengyi |
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Description: 基于密度的聚类算法
它将簇定义为密度相连的点的最大集合，能够把具有足够高密度的区域划分为簇，并可在噪声的空间数据库中发现任意形状的聚类(Density based clustering algorithm
It defines the cluster as the largest set of density connected points, and can divide the region with enough high density into clusters, and can find clusters of arbitrary shape in the spatial database of noise) Platform: |
Size: 3072 |
Author:微染 |
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Description: 矢量网络法散将射参数转化为介电常数
本代码计算需要的输入值为：d(超材料厚度方向的周期常数)，f(频率的变化范围)，S(通过CST或HFSS软件计算得到的散射参数)(The vector network dispersion transforms the radiation parameters into the dielectric constant
Input values required for calculation in this code are: D (periodic constant in the direction of metamaterial thickness), F (range of frequency variation), S(scattering parameters calculated by CST or HFSS software)) Platform: |
Size: 14336 |
Author:frredead |
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Search - DBSCAN in matlab