An improved algorithm for partial clustering

作者：

Highlights：

• Outlier detection is important for improving clustering results.

• Over detection of outliers leads to information loss.

• Our proposal reduces the number of over-detected outliers.

• Experiments show that clustering quality can be improved, while runtime is reduced.

摘要

•Outlier detection is important for improving clustering results.•Over detection of outliers leads to information loss.•Our proposal reduces the number of over-detected outliers.•Experiments show that clustering quality can be improved, while runtime is reduced.

论文关键词：Clustering,Estimation of the number of clusters,Outlier detection

论文评审过程：Received 28 February 2018, Revised 14 December 2018, Accepted 17 December 2018, Available online 19 December 2018, Version of Record 22 December 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.12.027