A new robust semi-supervised clustering method based on adaptive credibility estimation and locality preservation

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Hengdong Zhu, Rongjiao Liang, Baoshuo Kan, Enliang Yan, Fu Lee Wang, Tianyong Hao

Published: 01 Jan 2025, Last Modified: 11 Nov 2025Neurocomputing 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•Developed an adaptive credibility strategy to assess labeled-sample risk.•Proposed robust semi-supervised clustering CLSC addressing mislabeling.•Introduced discriminative projection preserving data structure integrity.•Extensive experiments validate state-of-the-art performance.