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Semi-Supervised Clustering for Financial Risk Analysis
Many methods have been developed for financial risk analysis. In general, the conventional unsupervised approaches lack sufficient accuracy and semantics for the clustering, and the supervised approaches rely on large amount of training data for the classification. This paper explores the semi-super...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8223531/ https://www.ncbi.nlm.nih.gov/pubmed/34188603 http://dx.doi.org/10.1007/s11063-021-10564-0 |