Classification with Incomplete Probabilistic Labeling Based on Manifold Regularization and Fuzzy Clustering Ensemble Full article
| Journal |
Pattern Recognition and Image Analysis
ISSN: 1054-6618 , E-ISSN: 1555-6212 |
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| Output data | Year: 2022, Volume: 32, Number: 3, Pages: 515-518 Pages count : 4 DOI: 10.1134/S1054661822030075 | ||
| Tags | cluster ensemble; fuzzy partitioning; low-rank matrix approximation; manifold regularization; probabilistic labeling; weakly supervised learning | ||
| Authors |
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| Affiliations |
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Funding (1)
| 1 | Russian Science Foundation | 22-21-00261 |
Abstract:
The paper proposes a weakly supervised binary classification method which combines manifold regularization and fuzzy clustering ensemble methodologies. We assume that the class labels can be fully supervised, defined in terms of a probability distribution or not specified at all. The co-association matrix of fuzzy clustering ensemble is used as the similarity matrix. This matrix is represented in a low-rank form that significantly speeds up calculations and saves memory. Numerical experiments using Monte Carlo modeling demonstrate the efficiency of the method.
Cite:
Berikov V.B.
, Vikent'ev A.A.
Classification with Incomplete Probabilistic Labeling Based on Manifold Regularization and Fuzzy Clustering Ensemble
Pattern Recognition and Image Analysis. 2022. V.32. N3. P.515-518. DOI: 10.1134/S1054661822030075 WOS Scopus РИНЦ OpenAlex
Classification with Incomplete Probabilistic Labeling Based on Manifold Regularization and Fuzzy Clustering Ensemble
Pattern Recognition and Image Analysis. 2022. V.32. N3. P.515-518. DOI: 10.1134/S1054661822030075 WOS Scopus РИНЦ OpenAlex
Dates:
| Submitted: | May 31, 2022 |
| Accepted: | May 31, 2022 |
| Published print: | Oct 19, 2022 |
| Published online: | Oct 19, 2022 |
Identifiers:
| Web of science: | WOS:000869886400011 |
| Scopus: | 2-s2.0-85140117752 |
| Elibrary: | 49604113 |
| OpenAlex: | W4306745292 |
Citing:
| DB | Citing |
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| Elibrary | 1 |