Abstract
The authors here show that machine learning techniques can be used for designing an archaeological typology, at an early stage when the classes are not yet well defined. The program (LEGAL, LEarning with GAlois Lattice) is a machine learning system which uses a set of examples and counter-examples in order to discriminate between classes. Results show a good compatibility between the classes such as the yare defined by the system and the archaeological hypotheses.
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Nguifo, E.M., Lagrange, MS., Renaud, M. et al. PLATA: An Application of LEGAL, a Machine Learning Based System, to a Typology of Archaeological Ceramics. Computers and the Humanities 31, 169–187 (1997). https://doi.org/10.1023/A:1000904004065
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DOI: https://doi.org/10.1023/A:1000904004065