Density Adaptive Parallel Clustering
This addresses clustering challenges for data analysis by offering an incremental improvement over existing methods.
The paper tackles the problem of clustering by introducing a new nearest neighbors-based algorithm that is deterministic, simpler, faster, and does not require pre-specifying the number of clusters, comparing it with previous solutions like DBscan and minimum spanning tree approaches.
In this paper we are going to introduce a new nearest neighbours based approach to clustering, and compare it with previous solutions; the resulting algorithm, which takes inspiration from both DBscan and minimum spanning tree approaches, is deterministic but proves simpler, faster and doesnt require to set in advance a value for k, the number of clusters.