Clustring by DBSCAN

C++ Implementation of clustering by DBSCAN

To run the implementation

1. Keep project files in one folder.

2. compile using command make.

To compile without using the makefile, type the following command.

g++ -std=c++11 clustering.cpp -o clustering.exe

(Note that -std=c++11 option is must be given in g++.)

3. Run using following command.

./clustering.exe [intput.txt] [n] [eps] [minPts]

Summary of the algorithm

Given a set D of objects, we identify all core objects w.r.t. the given parameters, ε (Eps) and MinPts.

• Arbitrary select an object o in D
• If o is a core point, a cluster is formed

Collect all objects density-reachable from o, w.r.t. Eps and MinPts (DBSCAN iteratively collects directly density-reachable objects)

• Merge of a few density-reachable clusters may occur
• If o is a border object, no objects are density-reachable from o and DBSCAN visits the next object of the database

If o is not density-reachable from any core point, p is considered to be noise and not added to any cluster

• Continue the process until all of the objects have been processed

Any other specification of the implementation and testing

• Note that I use c++11, not c++. therefore -std=c++11 option is must be given in g++.

input1: 98.91%

input2: 94.60%

input3: 99.97%