A model based on Bayesian confirmation and machine learning algorithms to aid archaeological interpretation by integrating incompatible data.

ABSTRACT: The interpretation of archaeological features often requires a combined methodological approach in order to make the most of the material record, particularly from sites where this may be limited. In practice, this requires the consultation of different sources of information in order to cross validate findings and combat issues of ambiguity and equifinality. However, the application of a multiproxy approach often generates incompatible data, and might therefore still provide ambiguous results. This paper explores the potential of a simple digital framework to increase the explanatory power of multiproxy data by enabling the incorporation of incompatible, ambiguous datasets in a single model. In order to achieve this, Bayesian confirmation was used in combination with decision trees. The r

SUBMITTER: Vos D 

PROVIDER: S-EPMC8011785 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature