No self-introduction
Loading
Profile
Follow
codes (1)
DBSCAN algorithm
no vote
% Function: [class,type]=dbscan(x,k,Eps)
% -------------------------------------------------------------------------
% Aim:
% Clustering the data with Density-Based Scan Algorithm with Noise (DBSCAN)
% -------------------------------------------------------------------------
% Input:
% x - data set (m,n); m-objects, n-variables
% k - number of objects in a neighborhood of an object
% (minimal number of objects considered as a cluster)
% Eps - neighborhood radius, if not known avoid this parameter or put []
% -------------------------------------------------------------------------
% Output:
% class - vector specifying assignment of the i-th object to certain
% cluster (m,1)
% type - vector specifying type of the i-th object
% (core: 1, border: 0, outlier: -1)
williamdou 0 0
1
No more~
Follows0
Fans0