Clustering biomedical and gene expression datasets with kernel density and unique neighborhood set based vein detection

作者：

Highlights：

• KUVClust does not require any user input to produce high quality clusters.

• KUVClust produces high quality clusters from biomedical & gene expression datasets.

• KUVClust is combination of three concepts namely Vein-based clustering, KDE and UNS.

• KUVClust works well on both high dimensional and low dimensional datasets.

摘要

•KUVClust does not require any user input to produce high quality clusters.•KUVClust produces high quality clusters from biomedical & gene expression datasets.•KUVClust is combination of three concepts namely Vein-based clustering, KDE and UNS.•KUVClust works well on both high dimensional and low dimensional datasets.

论文关键词：Clustering,Biomedical,Gene expression,Kernel density estimation,Vein-based clustering,Unique neighborhood set

论文评审过程：Received 11 September 2019, Revised 4 January 2020, Accepted 7 January 2020, Available online 23 January 2020, Version of Record 29 January 2020.

论文官网地址：https://doi.org/10.1016/j.is.2020.101490