Description: 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是全部算法的实现文件，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。-Form1.cs clustering algorithm is applied DBSCAN (Density-Based S patical Clustering of Application with Noise) example, the two parameters can EPS and MinPts regulation clustering. DBSCAN.cs algorithm is the realization of all documents, the clustering algorithm further information please refer to the "data mining" or books. Clustering sample data from sxdb.mdb, an Access database. Platform: |
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Author:yang |
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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. Platform: |
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Author: |
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Description: 用c++实现的CURE聚类算法 这是即DBSCAN算法后出现的基于密度的聚类算法-With c++ Realized CURE clustering algorithm DBSCAN algorithm that is, this is occurring after the density-based clustering algorithm Platform: |
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Author:刘年 |
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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: |
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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: |
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Author:sdc |
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Description: 实验目的
1.对AIS数据按照上行、下行船舶轨迹点进行分类。
2.掌握基于密度聚类方法原理（以DBSCAN为例）。
3.熟悉AIS数据处理的基本方法。
4.熟悉船舶运动模式辨识的基本原理和方法。
实验环境
Matlab(Purpose
1. The AIS data are classified according to the upstream and downstream ship's track points.
2. Master the principle of density clustering based on DBSCAN as an example.
3. Familiar with the basic method of AIS data processing.
4. Familiar with the basic principles and methods of ship movement pattern identification.
lab environment
Matlab) Platform: |
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Author:benj
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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: |
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Author:zkzfengyi |
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Description: 给出基于密度的聚类之DBScan算法的具体思想和Matlab实现步骤(The idea of DBScan algorithm based on density clustering and the steps of Matlab are given) Platform: |
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Author:皮皮时光机 |
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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: |
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Author:微染 |
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Search - density based clustering dbscan matlab