Abstract— Existing clustering ensemble algorithms for partitioning data need to know the generating process of clustering members clearly and most of them ...

Abstract—Existing clustering ensemble algorithms for partitioning data need to know the generating process of clustering members clearly and most of them are ...

This paper tries to propose an ensemble aggregator, or a consensus function, called as Robust Clustering Ensemble based on Sampling and Cluster Clustering ( ...

So after the grid search, we obtain a large number of partitionings. We break any of the partitionings into its clusters, and then they form an ensemble of ...

Clustering ensemble selection chooses a subset of ensemble members and forms a smaller cluster ensemble that performs better than the clustering ensemble.

Apr 1, 2023 · In this paper, we propose a Random Sample Partition-based Centers Ensemble (RSPCE) algorithm to identify the number of clusters in a big dataset.

Jul 1, 2010 · Fuzzy Clustering Ensemble with Selection of Number of Clusters // Journal of Computers. 2010. Vol. 5. No. 7. GOST all authors (up to 50) ...

Aug 3, 2024 · This paper proposes a novel clustering ensemble approach for improving the robustness and accuracy of the MKFC algorithm.

Km is the number of fuzzy clusters constructed by that member. The fuzzy clusters generated by all ensem- ble members together form a set of fuzzy base clusters.

In this paper, to compensate for the mentioned weakness a new fuzzy clustering ensemble approach has been proposed using a weighting strategy at fuzzy cluster ...