Sparse Subspace Learning Based on Learnable Constraints for Image Clustering

Article Computer Science, Information Systems

Multi-view spectral clustering for uncertain objects

Krishna Kumar Sharma et al.

Summary: Uncertain data clustering is a crucial task in machine learning and pattern recognition. Multi-view clustering has gained attention for producing good results compared to single-view clustering, with the introduction of a self-adaptive mixture similarity measure (SAM) to address limitations of existing similarity measures. Experimental results show that SAM outperforms state-of-the-art methods in grouping uncertain data.

INFORMATION SCIENCES (2021)

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Article Computer Science, Artificial Intelligence

Spectral embedded generalized mean based κ-nearest neighbors clustering with S-distance

Krishna Kumar Sharma et al.

Summary: The spectral clustering algorithm is widely used in the field of pattern recognition, with the efficient construction of the neighborhood graph being a key factor in obtaining promising results. This study integrates S-distance to uncover complex and non-linear cluster structures. By proposing improvements in the selection of KNN and construction of the neighborhood graph, the impact of outliers and noise in the data is reduced.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

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Article Multidisciplinary Sciences

An Enhanced Spectral Clustering Algorithm with S-Distance

Krishna Kumar Sharma et al.

Summary: In this study, a churn prediction framework is developed using modified spectral clustering, which improves churn prediction accuracy by using non-linear S-distance and analyzing industrial data. The proposed clustering algorithm outperforms existing algorithms in terms of Jaccard index, f-score, recall, precision, and accuracy, especially for clusters of arbitrary shape.

SYMMETRY-BASEL (2021)

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Article Computer Science, Artificial Intelligence