Density-ratio based clustering for discovering clusters with varying densities

作者：

Highlights：

• Analyse a key weakness of density-based clustering algorithms.

• Introduce two approaches based on density-ratio to overcome this weakness.

• ReCon converts an existing density estimator to a density-ratio estimator.

• ReScale transforms a dataset by an adaptive scaling based on density-ratio.

• ReCon and ReScale approaches improve three density-based clustering algorithms.

摘要

Highlights•Analyse a key weakness of density-based clustering algorithms.•Introduce two approaches based on density-ratio to overcome this weakness.•ReCon converts an existing density estimator to a density-ratio estimator.•ReScale transforms a dataset by an adaptive scaling based on density-ratio.•ReCon and ReScale approaches improve three density-based clustering algorithms.

论文关键词：Density-ratio,Varying densities,Density-based clustering,Scaling

论文评审过程：Received 22 July 2015, Revised 23 May 2016, Accepted 3 July 2016, Available online 5 July 2016, Version of Record 29 July 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.07.007