Analysis and identification of ancient glass artifacts based on component data

This study explores the classification of glass artifacts based on their chemical composition. Using the stratified chi-square test method, the correlation between the chemical characteristics of glass artifacts and their susceptibility to weathering was analyzed. A decision tree model was constructed to predict and analyze the types of glass artifacts. To further study the types of glass artifacts, factor analysis was employed to reduce the dimensionality of the data, simplifying the data structure. Based on the reduced data, the K-means clustering algorithm was used to further classify the glass artifacts into three subcategories.