In this paper, we introduce the fuzzy theory into the structure framework and propose a newfangled double fuzzy c-means structure ensemble framework, named as ...

In this paper, we introduce the fuzzy theory into the structure framework and propose a newfangled double fuzzy c-means structure ensemble framework, named as ...

In this paper, we introduce the fuzzy theory into the structure framework and propose a newfangled double fuzzy c-means structure ensemble framework, named as ...

Sep 30, 2021 · This work proposes a bi-directional FCM clustering ensemble technique that takes local information into account (LI_BIFCM) to address the drawbacks of FCM.

Following such recent development, this paper presents a link-based hierarchical consensus-based approach for building ensembles of fuzzy c-means. The resulting ...

Feb 15, 2022 · A new robust fuzzy c-means clustering method based on adaptive elastic distance (ARFCM) for image segmentation was proposed.

In this paper, a dominant-set-based consensus method for fuzzy-c-means-based clustering ensemble is proposed. Dif- ferent from traditional graph-based ...

Missing: Structure | Show results with:Structure

In this paper, an academic analysis of influences of random projection on the variability of data set and the dependence of dimensions has been proposed.

An under-sampling ensemble classification algorithm based on Fuzzy C-Means clustering for imbalanced data.