Divide well to merge better: A novel clustering algorithm
作者：
Highlights：
• A novel non-parametric clustering algorithm based on the concept of divide-and-merge.
• Ability to discover both convex and non-convex shaped clusters.
• Ability to discover clusters different in densities.
• Ability to detect and remove outliers/noise in the data.
• Usability for high dimensional data and easily tunable or fixed hyperparameters.
摘要
•A novel non-parametric clustering algorithm based on the concept of divide-and-merge.•Ability to discover both convex and non-convex shaped clusters.•Ability to discover clusters different in densities.•Ability to detect and remove outliers/noise in the data.•Usability for high dimensional data and easily tunable or fixed hyperparameters.
论文关键词：Clustering,Data projection,Joint probability density estimation,Non-parametric techniques
论文评审过程：Received 4 May 2021, Accepted 6 September 2021, Available online 8 September 2021, Version of Record 20 September 2021.
论文官网地址：https://doi.org/10.1016/j.patcog.2021.108305
