Since many existing distance-based clustering algorithms have a bias towards dense clusters, the proposed methods are used to “correct” this bias, based on the concept of “density-ratio”.
- modify a density-based clustering algorithm to do density-ratio based clustering by using its density estimator to compute density-ratio. The modified DBSCAN for density-ratio based clustering can be obtained from here.
- rescaling the given dataset to make equalise different clusters' densities, then a standard density-estimator can directly perform density-ratio estimation on the transformed dataset. The feature individual scaling method ReScale can be obtained from here, a multi-dimensional distance scaling method DScale can be obtained from here, and the latest data transformation method CDF-TS can be obtained from here.