Fondazione GRINS
Growing Resilient,
Inclusive and Sustainable
Galleria Ugo Bassi 1, 40121, Bologna, IT
C.F/P.IVA 91451720378
Finanziato dal Piano Nazionale di Ripresa e Resilienza (PNRR), Missione 4 (Infrastruttura e ricerca), Componente 2 (Dalla Ricerca all’Impresa), Investimento 1.3 (Partnership Estese), Tematica 9 (Sostenibilità economica e finanziaria di sistemi e territori).
Open Access
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This study focuses on adapting spectral clustering, a numeric data-clustering technique, for categorical and mixed-type data. The method enhances spectral clustering for categorical and mixed-type data with novel kernel functions, showing improved accuracy in real-world applications. Despite achieving better clustering for datasets with mixed variables, challenges remain in identifying suitable kernel functions for categorical relationships.
AKNOWLEDGEMENTS
This study was funded by the European Union - NextGenerationEU, in the framework of the GRINS - Growing Resilient, INclusive and Sustainable project (GRINS PE00000018). The views and opinions expressed are solely those of the authors and do not necessarily reflect those of the European Union, nor can the European Union be held responsible for them.
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