graphs-10

Clustering Ensemble

3260 papers • 126 benchmarks • 313 datasets

This task has no description! Would you like to contribute one?

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in clustering-ensemble-10

Trend

Dataset

Best Model

Actions

pathbased

ionosphere

Libraries

i

Use these libraries to find clustering-ensemble-10 models and implementations

Datasets

ionosphere

pathbased

Subtasks

No subtasks available.

Most implemented papers

The Impact of Random Models on Clustering Similarity

Alexander J. Gates, Yong-Yeol Ahn•Sun Jan 22 2017

It is demonstrated that the choice of random model can have a drastic impact on the ranking of similar clustering pairs, and the evaluation of a clustering method with respect to a random baseline; thus, the choices of random clustering model should be carefully justified.

141

Content

0

Paper Graph

An Internal Validity Index Based on Density-Involved Distance

Lianyu Hu, Caiming Zhong•Thu Mar 21 2019

A new robust distance measure, one into which density is incorporated, is designed to solve the problem, and an internal validity index based on this separation measure is then proposed, which can cope with both the spherical and non-spherical structure of clusters.

40 0

Paper Graph

Clustering Ensemble Meets Low-rank Tensor Approximation

Junhui Hou, Qingfu Zhang, Yuheng Jia, Hui Liu•Tue Dec 15 2020

A novel low-rank tensor approximation based method to solve the problem of clustering ensemble from a global perspective, which is fundamentally different from previous approaches and achieves a breakthrough in clustering performance, compared with 12 state-of-the-art methods.

39 0

Paper Graph

Ensemble clustering based on evidence extracted from the co-association matrix

Lianyu Hu, Caiming Zhong, Haiyong Xu, Xiaodong Yue, Ting Luo, Qiang Fu•Wed Jul 31 2019

This paper removes multiple level evidences having low occurrence frequencies from the co-association matrix, and uses normalized cut to achieve multiple clustering results, demonstrating that the proposed scheme outperforms some state-of-the-art clustering ensemble approaches.

32 0

Paper Graph

Adding a benchmark result helps the community track progress.