Cardarelli, Lorenzo and Lapadula, Annalisa (2022) Dimensionality reduction for data visualization and exploratory analysis of ceramic assemblages. Archeologia e Calcolatori, 33 (2). pp. 33-52. ISSN 1120-6861
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Abstract
Size reduction algorithms are essential in the study of multivariate datasets. Many variables make it difficult to visualize data. In Archaeology, this problem often concerns the study of some variables, which can be quantitative or qualitative. In this article, several methods for dimension reduction are applied to a pottery dataset from the protohistoric necropolis Osteria dell'Osa, located 20 km East of Rome. These methods offer the possibility of visualising and analysing large amount of data in a very short time. Our results show that non-linear and non-parametric algorithms such as t-SNE and UMAP are the best choice for visualising and exploring this type of data.
| Item Type: | Article |
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| Additional Information: | Licensed under CC BY-NC-ND 4.0 |
| Uncontrolled Keywords: | Statistics; Classification of archaeological finds |
| Subjects: | 900 Storia, Geografia e discipline ausiliarie > 930 Storia dei mondo antico fino al 499 ca. > 930.1 Archeologia (Classificare qui la Storia fino al 4000 a.C., l'Archeologia preistorica, le opere interdisciplinari sull'Archeologia) > 930.102 Archeologia - Opere miscellanee > 930.1028 Archeologia – Tecniche, metodologie, apparecchi e strumenti (comprende: Archeometria) > 930.10285 Archeologia – Applicazioni informatiche (comprende: tecniche di datazione) |
| Depositing User: | Dott.ssa Paola Moscati |
| Date Deposited: | 29 Jul 2024 13:48 |
| Last Modified: | 29 Jul 2024 13:48 |
| URI: | http://eprints.bice.rm.cnr.it/id/eprint/23034 |
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