The relevant data of a batch of glass artifacts

Published: 6 May 2025| Version 1 | DOI: 10.17632/6sb4y5d6kc.1
Contributor:
Z G Deng

Description

The data contains the glass type, emblazonry, colors, weathering states and component proportion of surface sampling points of a batch of glass artifacts. The data also contains the unweathered component proportion of weathered glass artifacts predicted by machine learning algorithms. The data also includes the training process of the machine learning algorithms and the final model parameters, as well as the available trained models.

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Steps to reproduce

Establish a logistic regression model to predict the weathering state and weathering degree of glass artifacts. Combining the differences in component proportion and weathering degree of glass artifacts in the two states, the data of component proportion of weathered glass artifacts without weathering was predicted.

Institutions

Central Iron and Steel Research Institute Group

Categories

Archeological Glass

Licence