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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
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Size: 26624 |
Author: Huang Yi |
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Description: DBSCAN算法的JAVA实现,可以在D:\使用text.txt数据文件来进行DBSCAN聚类-DBSCAN algorithm JAVA, the D : \ text.txt data files used for clustering DBSCAN
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Size: 16384 |
Author: 赵发毅 |
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Description: 聚类算法，k-means和dbscan算法-Clustering algorithm, k-means algorithm and dbscan
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Size: 15360 |
Author: heyueqiang |
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Description: 基于密度的聚类的实现，用JSP实现的，界面友好-Density-based clustering to achieve, using JSP to achieve, user-friendly
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Size: 5120 |
Author: 赵妍 |
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Description: 数据挖掘,聚类分析,DBSCAN JAVA的实现,
-Data mining, clustering analysis, DBSCAN JAVA realization
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Size: 216064 |
Author: wang |
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Description: DBSCAN的Java 数据挖掘 源代码-DBSCAN the Java Data Mining Source Code
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Size: 3830784 |
Author: 林春 |
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Description: 用java写的DBscan算法，支持文本读入，并且结果可以用图像显示的-With DBscan algorithm written in java, read text, and the results can be graphically
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Size: 2048 |
Author: Calvin Chen |
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Description: DBscan clustering algorithm source code in java
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Size: 7168 |
Author: kiran |
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Description: This is a manual for dbscan algorithm
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Size: 35840 |
Author: dogukan |
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Description: Density Based Spatial Clustering of Applications of Noise
Uses a density-based notion of clusters to discover clusters of arbitrary shapes, in spatial databases
Key idea: for each object of a cluster, the neighborhood of a given radius contains at least a minimum number of data-objects. (i.e. the density of each cluster must exceed a threshold value)
Choosing the distance function is the critical parameter.
An object that appears to be part of Noise at present, might, at a later stage, be included into one of the clusters.
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Size: 4096 |
Author: nandish.hebbal |
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Description: 基于密度的聚类算法 JAVA实现 能发现任何形状的聚类-JAVA-based density clustering algorithm can be found in any shape to achieve the clustering
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Size: 2048 |
Author: 龙君 |
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Description: Java DBSCAN clustering algorithm source code
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Size: 7168 |
Author: tran thang |
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Description: dbscan in java
cara melakukan clluster db scan dengan java
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Size: 3072 |
Author: afif suaidi |
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Description: 基于相对密度的聚类算法（DBSCAN算法），用于处理高密度簇完全被相连的低密度簇所包含的问题-Clustering algorithm based on relative density (DBSCAN algorithm), to handle high-density clusters are completely connected to the problem of low-density cluster contains
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Size: 3072 |
Author: MAHY |
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Description: DBSCAN AND CURE Data Mining in Java
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Size: 115712 |
Author: sam |
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Description: dbscan in java .. compressed in .rar ..full implementation of density based clustering
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Size: 47104 |
Author: appu |
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Description: DBScan算法实现，用Java高级编程语言正确实现DBSCAN算法，DBScan是一种基于密度的聚类算法，它有一个核心点的概念：如果一个点，在距它e的范围内有不少于MinP个点，则该点就是核心点。核心和它e范围内的邻居形成一个簇。在一个簇内如果出现多个点都是核心点，则以这些核心点为中心的簇要合并。最终输出找到的簇及其数据点。-DBScan algorithm, using high-level programming language Java is implemented correctly DBSCAN algorithm, DBScan is a clustering algorithm based on density, it has the concept of a core point: if a point in the range its e has a less than MinP point, the point is the core point. E Core and neighbors within the range which forms a cluster. Within a cluster If multiple points are key points, places these core point in the center of the cluster to be merged. Its final output cluster data points found.
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Size: 11264 |
Author: 热风 |
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Description: Java implementation for DBSCANSD, a trajectory clustering algorithm.
DBSCANSD (Density-Based Spatial Clustering of Applicationswith Noise considering Speed and Direction)[1] is a clustering algorithm extended from DBSCAN [2]. It can consider speed and direction, which is essential for maritime lanes extraction. The output of this algorithm is a set of Gravity Vectors (GV) and Sampled Stopping Points (SSP).
In the present version, the implementation has not included generating SSP yet, but I shall add this part later.
Since the AIS data provided for this project is confidential, I cannot upload it to github as example. But I generated a toy data set and put it in the src folder which can be tested with the program. And it will be great if you use this algorithm for other domains' problems, such as tracking data of vehicles, pedestrian, hurricane or animals.
More details about this algorithm can be found in [1]. The link is as following:
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7004281
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Size: 2772182 |
Author: 648577896 |
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Description: # How To Run The Code ?
After downloading it to local,
1. cd to the folder of src/boliu/dbscansd/
2. compile all the .java files using:
javac *.java
3. cd to the folder of src/
4. execute the program using the following either command:
java boliu.dbscansd.Main inputfile outputfile lineNum eps minPts maxSpd maxDir isStop
* @param inputfile the input file path
* @param outputfile the output file path
* @param lineNum the designated number of trajectory points for clustering (if the size of the input file is less than lineNum, it will extract all the points)
* @param eps 1st parameter of DBSCANSD, the radius
* @param minPts 2nd parameter of DBSCANSD, the minimum number of points
* @param maxSpd 3rd parameter of DBSCANSD, the maximum SOG difference
* @param maxDir 4th parameter of DBSCANSD, the maximum COG difference
* @param isStop boolean value (0/1), if you would like to cluster stopping points (1) or moving points (0)
--e.g. java boliu.dbscansd.Main toy_data.csv output 70000 0.03 50 2 2.5 0
In this way, the program will do the job on toy_data.csv file.
It will extract the first 70,000 moving points from the data and then run DBSCANSD on the dataset.
The final output will be two files:
output_gv.csv (gravity vectors)
output_movingclusters.csv (original clustering results with more rows).
5. waiting for the result :) The running time will vary with different sizes of the input data and other input parameters.
6. Star it if it helps \*-\*
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Size: 11994582 |
Author: 648577896 |
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