Python implementation of a weighted extension of DBSCAN (Ester et al., 1996).
This module provides a weighted implementation of Ester et al.'s algorithm, accomodating instance weights. Here, a core object is not defined as an object whose epsilon-neighborhood contains at least a given number of objects, but as an object whose epsilon-neighborhood weighs a least a given weight. The weight of a given object's epsilon-neighborhood is straightforwardly defined as the sum of the weights of its epsilon-neighbors. This implementation does not require weights to be positive, so be careful what you wish for, you might just get it.
To use this module, you must have NumPy installed.
Do What The Fuck You Want To Public License (version 2).
When using wdbscan for a publication, please cite my doctoral dissertation.
@phdthesis{
author = {Boruta, Luc},
title = {Indicators of Allophony and Phonemehood},
school = {Universit{\'e} Paris Diderot},
year = {2012},
}