Discovering Prehistoric Ritual Norms. A Machine Learning Approach
| Autor: | Duboscq, Stephanie, Barceló-Álvarez, Juan Antonio, Achino, Katia, Morell, Berta, Alliése, F., Gibaja, Juan Francisco |
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| Rok vydání: | 2016 |
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| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname |
| Popis: | In this paper we propose a computational approach, based on the application of supervised learning techniques, in order to understand prehistoric funerary practices. In particular we focus on the understanding of relevant ritual pattems from North-Eastem Iberian Peninsula Middle Neolithic burials. We compare standard statistical multidimensional approaches with machine learning methods based on a supervised learning approach in which the relevant category to be formally induced is the sex of the individuals. Different analysis will be explored, as Cluster and Correspondence analysis and Decision Trees to show how we can define social norms in the archaeological record based on detecting relevant differences between controlled categories. Of special relevance for our purposes is the comparison between 'classical ' Confirmatory Factor Analysis ofburial similarities and the machine learning approach to conceptual induction. |
| Databáze: | OpenAIRE |
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